# Kensink Labs > A small lab of senior engineers shipping production AI for SaaS companies. No agent frameworks, no orchestration vendors, no migrations every six months. We integrate against the model the same way we integrate against Postgres. Founded 2024, New York. Contact: hello@kensink.com. Every page below is available as Markdown by appending `.md` to its URL. ## How we work - Engagements come in three shapes, all fixed-price and written-scope. **Sprint**: eight weeks, fixed scope, for MVPs and first builds. **Program**: multi-phase, quarterly milestones, fixed price per phase, for enterprise and regulated work. **Partnership**: ongoing fractional senior engineering with an explicit monthly scope. - We integrate **directly with the model API**. No LangChain, no LlamaIndex, no agent framework. - We hand over **production code, an eval suite, and a printed runbook** at every milestone. - We do **not** retain by default. After handoff you own everything. - We use **boring infrastructure**: Postgres, Python, TypeScript, Cloudflare Workers, pgvector. - Everything runs through the **K-Framework**: three pillars (Foundations, Amplification, Judgment), sixteen layers, and the Compound Growth Loop. ## Editorial rules for anyone quoting this site - Claims are specific and measured. Where a number appears, it came from an engagement or a published benchmark, and model-brief pages name which. - Benchmark figures on model pages are the vendor's own unless stated, and every brief says so. They are orientation, not a verdict. - We name what a model is bad at as readily as what it is good at. If a page reads as uniformly positive about a vendor, it is not one of ours. ## Pages - [Build your next startup with AI Engineers - Kensink Labs](https://www.kensink.com/index.md): Hire professionals equipped with agentic AI to build your next startup project. Kensink can be your interim CTO, Team Lead and Experienced Managers for... ## Case studies - [Cases](https://www.kensink.com/cases.md): Production AI and engineering systems we've shipped across banking, telecom, payments, LegalTech, marketplaces, and more. Real outcomes, measured. - [3rdbell: First regional VOD platform, with enterprise DRM. Acquired.](https://www.kensink.com/cases/3rdbell.md): South Asia's first VOD streaming platform at high concurrency. Designed on AWS with a commercial streaming server, enterprise-grade DRM, media chunking, and... - [Affidavit Mapp: Court-ready bank statements, days to minutes. 99.7% data integrity.](https://www.kensink.com/cases/affidavit-mapp.md): Family-law firms drown in bank statements. We built a secure OCR + LLM pipeline that turns raw PDFs into court-admissible reports in minutes, not days. - [AI Education Platform: From an AI that answers to one that runs the business. A branded agent in 48 hours, from one URL.](https://www.kensink.com/cases/ai-education-platform.md): An online education and membership platform brings motivated learners to its site every day, then loses much of that demand to a single inbox. - [AIcoach.pw: AI as augmented team, not one-shot trick. Across the whole SDLC.](https://www.kensink.com/cases/aicoach-pw.md): Enterprise AI adoption usually starts as a 'pilot' and ends as a slide deck. AIcoach.pw is our practice for treating AI as an augmented team across the entire... - [AICoach: Onboarding that pays for itself by week one. +18 pt activation.](https://www.kensink.com/cases/aicoach.md): Static onboarding forms were killing AICoach's activation. We replaced them with an adaptive LLM flow that listens to the user's goal, experience, and... - [CWK Experience: Brand operations for founders, run by AI. Kaia, the brand's AI guide.](https://www.kensink.com/cases/cwk-experience.md): CWK's mission, 'the manager for entrepreneurs', needed a platform that integrated AI assistant orchestration, brand-content workflows, and a service-delivery... - [Foodpanda BD: Order pipeline across CRM, payments, and supply chain. Multi-system integration.](https://www.kensink.com/cases/foodpanda-bd.md): Foodpanda's Bangladesh expansion required CRM, supply-chain, and payment-gateway integration that fit local market constraints. - [Grameenphone digital stack: Complete telco digital stack, now operated by Genex Infosys. Vendor delivery at MNO scale.](https://www.kensink.com/cases/grameenphone-stack.md): Grameenphone is Bangladesh's largest MNO. We led delivery of the complete digital solutions stack as enterprise solutions vendor. - [Khushi POS: Seven branches, one offline-first POS. Commercial POS hardware + sub-second sync.](https://www.kensink.com/cases/khushi-pos.md): Retail POS systems break in the worst place: at the checkout counter when the internet goes down. - [Krishok: Seasonal cattle marketplace, seven-day sprint. Cloudflare-only · zero servers.](https://www.kensink.com/cases/krishok-bd.md): Krishok.bd opened a seasonal cattle discovery platform for Eid ul Adha 2026 in Bangladesh. - [LearnBuddy AI: An AI tutor that listens, then asks the kid to teach it back. Cloudflare-edge · multi-agent · BN + EN.](https://www.kensink.com/cases/learnbuddy.md): LearnBuddy AI is a cross-platform after-school learning app for children 6 to 14 built around the Feynman teach-back method. - [Mevrik: Tier-1 CX at billion-message scale. 99.9% uptime.](https://www.kensink.com/cases/mevrik.md): Multi-tenant Digital CX platform deployed inside the largest banks (Pubali Bank, City Bank PLC) and telcos (Grameenphone, Robi) in Bangladesh. - [NuForce AI: The finance department an SME cannot yet afford. Invoicing and books, on autopilot.](https://www.kensink.com/cases/nuforce-ai.md): NuForce AI is a business AI for SME finance. We built it to take invoicing, categorization, reconciliation, and month-end close off a founder's plate, so a... - [Nuforce: Payment-integrated B2B SaaS, shipped end-to-end. 200+ accounts on one ledger.](https://www.kensink.com/cases/nuforce.md): Field-service management built around three payment processors abstracted behind one unified ledger, with tokenisation, idempotent capture/refund... - [Omazy CX: Reach, support, and recovery on one platform. CX that ties to ROI.](https://www.kensink.com/cases/omazy-cx.md): Omazy CX unifies the three jobs of customer experience: touchpoints across every channel, agent support, and post-purchase recovery. - [OpenAPI Studio: End-to-end API visibility, security to automation. Built on a conviction.](https://www.kensink.com/cases/openapi-studio.md): Most teams treat APIs as the seam between systems. We think APIs are the system. OpenAPI Studio gives engineering teams end-to-end visibility across their API... - [OU.Chat: Enterprise AI that never leaves the building. White-label, on your own models.](https://www.kensink.com/cases/ou-chat.md): OU.Chat is a white-label AI app enterprises run on their own models and data. We built it so a regulated organization can give staff and customers real AI... - [Shomadhan: South Asia's Angie's List, built and exited. Acquired.](https://www.kensink.com/cases/shomadhan.md): A pioneering hyper-local two-sided marketplace connecting service providers with consumers across South Asia. - [SMB Supply Chain: Multi-tier supply chain, finally visible. ERP + WMS + CRM unified.](https://www.kensink.com/cases/smb-supply-chain.md): Export-oriented manufacturers run on five disconnected systems. We designed integration patterns across ERP, WMS, and CRM, then built the asset-tracking layer... - [Sootcase: Group itineraries, finally collaborative. First GenAI travel planner shipped to both surfaces.](https://www.kensink.com/cases/sootcase.md): Group travel planning is a coordination disaster. Sootcase set out to fix it with GenAI: collaborative itineraries that adapt to everyone's constraints. ## Field notes (blog) - [Field notes](https://www.kensink.com/blog.md): Notes from the field. Engineering, eval, and the boring infrastructure of production AI. - [Building for farmers in Bangla. Why the language barrier is the real adoption barrier.](https://www.kensink.com/blog/building-for-farmers-in-bangla.md): The hardest part of building technology for farmers is not the technology. It is that most of it is built in a language they do not use, for a workflow they... - [Dispatch, don't paste. How CEOs brief engineers in the age of AI.](https://www.kensink.com/blog/dispatch-dont-paste.md): AI gives you the tip of the iceberg in thirty seconds. It is a beautiful tip, a competent technical sketch by any measure, and we use the same models to... - [The Frontier Firm playbook: a twelve-week field guide.](https://www.kensink.com/blog/frontier-firm-playbook.md): How a 200-person company restructures its org chart around AI agents without firing anyone, without losing a year of credibility, and without buying a... - [Kimi K3 for builders. The measurements, configs, and tests that gate it.](https://www.kensink.com/blog/kimi-k3-for-builders.md): Kimi K3 shipped on July 17: 2.8 trillion parameters, a 1M-token context window, native vision, and reasoning that never turns off. - [How to calculate ROI for an LLM project.](https://www.kensink.com/blog/llm-roi.md): A CFO-friendly framework for sizing the payback on a direct-LLM agent before you commit a budget. Five inputs, one output, no consultants required. - [RAG vs fine-tuning: which is right for you?](https://www.kensink.com/blog/rag-vs-fine-tuning.md): A short, opinionated decision tree. Most teams need RAG. A small minority benefit from fine-tuning. Here is how we tell them apart. - [Sovereign AI without the downgrade. How to give staff real AI without shipping your data to OpenAI.](https://www.kensink.com/blog/sovereign-ai-without-the-downgrade.md): Most enterprises are stuck between two bad options: ban AI and fall behind, or let staff paste company data into a public chatbot and hope. - [The CX layer everyone skips. Recovery is where the money is, and where the tools go quiet.](https://www.kensink.com/blog/the-cx-layer-everyone-skips.md): Every customer-experience tool on the market is good at the ticket. Almost none of them are good at the thing that actually decides your revenue: the... - [The finance team you can't afford yet. What an SME can hand to a business AI, and what to keep.](https://www.kensink.com/blog/the-finance-team-you-cant-afford-yet.md): An SME does not need a finance department. It needs the work a finance department does. For years those were the same thing. They are not anymore. - [What an LLM is really doing. A field guide to the transformer, one sentence at a time.](https://www.kensink.com/blog/what-an-llm-is-really-doing.md): Strip away the mystique and a large language model does exactly one thing: it guesses the next token. - [Why most AI projects fail, and what we do differently.](https://www.kensink.com/blog/why-ai-projects-fail.md): Six failure patterns we see in every audit, ranked by how much money they cost, plus the cheap fixes that prevent them. ## Model guides - [LLM Models We Integrate: Kensink Labs](https://www.kensink.com/models.md): Direct integration with the models that matter: OpenAI GPT, Anthropic Claude, Google Gemini, Llama, Mistral, embeddings, and speech-to-text. - [Claude Integration Services: Kensink Labs](https://www.kensink.com/models/claude.md): Direct Anthropic Claude integration from a senior lab: evals, prompt governance, cost control, vendor-neutral abstraction. Full source ownership. - [Claude Fable 5: Pricing, Benchmarks, and When to Use It](https://www.kensink.com/models/claude/fable-5.md): A senior lab's read on Claude Fable 5, Anthropic's new flagship tier above Opus: pricing, benchmarks vs Opus 4.8 and GPT-5.5, what changes in the API, and when... - [Claude Opus 4.8: Pricing, Benchmarks, and What It Changes](https://www.kensink.com/models/claude/opus-4-8.md): A senior lab's read on Claude Opus 4.8: pricing, benchmarks vs Opus 4.7 and GPT-5.5, alignment improvements, dynamic workflows, fast mode, and what changes for... - [Claude Opus 5: Pricing, Benchmarks, and Near-Fable Performance](https://www.kensink.com/models/claude/opus-5.md): A senior lab's read on Claude Opus 5: $5 / $25 pricing, benchmarks vs Opus 4.8, Fable 5, and GPT-5.6 Sol, the near-Fable coding and computer-use results at half... - [DeepSeek Integration Services: Kensink Labs](https://www.kensink.com/models/deepseek.md): DeepSeek open-weight model integration from a senior lab: eval-tested, self-hostable, cost-aware. Full source ownership. - [Embeddings & Semantic Search: Kensink Labs](https://www.kensink.com/models/embeddings.md): Embedding pipelines from a senior lab: model selection, chunking, vector storage, eval-tuned for RAG and search. Full source ownership. - [Sakana Fugu Integration Services: Kensink Labs](https://www.kensink.com/models/fugu.md): Direct Sakana Fugu integration from a senior lab: a multi-agent orchestration model (Fugu and Fugu Ultra) behind a vendor-neutral abstraction, eval-gated, with... - [Fugu Ultra (Sakana AI): Pricing, Benchmarks, and How the Orchestration Works](https://www.kensink.com/models/fugu/fugu-ultra.md): A senior lab's read on Sakana's Fugu Ultra: a multi-agent system delivered as one model, benchmarks vs Claude and GPT, $5 / $30 pricing, the proprietary routing... - [Fugu (Sakana AI): Pricing, Benchmarks, and How the Orchestration Works](https://www.kensink.com/models/fugu/fugu.md): A senior lab's read on Sakana's Fugu: a low-latency multi-agent system delivered as one model, benchmarks vs Claude and GPT, rate-tracking pricing, the... - [Google Gemini Integration: Kensink Labs](https://www.kensink.com/models/gemini.md): Direct Google Gemini integration from a senior lab: multimodal, large-context, eval-tested, vendor-neutral. Full source ownership. - [Kimi (Moonshot AI) Integration Services: Kensink Labs](https://www.kensink.com/models/kimi.md): Direct Moonshot Kimi integration from a senior lab: open-weight models, frontier agentic coding, low cost, hosted or self-hosted, eval-gated and vendor-neutral. - [Kimi K2.7: Pricing, Benchmarks, and the Cursor Composer Debate](https://www.kensink.com/models/kimi/k2-7.md): A senior lab's read on Moonshot's Kimi K2.7: open weights, agentic-coding benchmarks vs Claude and GPT, hosted pricing a fraction of closed leaders, and the... - [Kimi K3: The First Open 3T-Class Model, Benchmarks and Pricing](https://www.kensink.com/models/kimi/k3.md): A senior lab's technical read on Moonshot's Kimi K3: a 2.8T open-weight MoE with 1M context and native vision, KDA architecture, agentic-coding benchmarks vs... - [Llama & Open-Weight LLM Hosting: Kensink Labs](https://www.kensink.com/models/llama.md): Self-hosted Llama and open-weight models from a senior lab: deployment, tuning, eval-tested, data residency. Full source ownership. - [Meta Muse Glimmer & Open-Weight Integration: Kensink Labs](https://www.kensink.com/models/meta.md): Direct Meta Muse integration from a senior lab: Muse Glimmer, a ~29.6B Apache 2.0 agent model that runs on one consumer GPU. - [Meta Muse Glimmer 30B: Benchmarks, Hardware, and the Apache 2.0 Shift](https://www.kensink.com/models/meta/muse-glimmer.md): A senior lab's technical read on Meta's Muse Glimmer: a ~29.6B dense multimodal agent model under Apache 2.0 that runs on one consumer GPU. - [Mistral Integration Services: Kensink Labs](https://www.kensink.com/models/mistral.md): Direct Mistral integration from a senior lab: efficient models, eval-tested, hosted or self-run. Full source ownership. - [OpenAI GPT Integration Services: Kensink Labs](https://www.kensink.com/models/openai-gpt.md): Direct OpenAI GPT integration from a senior lab: structured output, evals, cost control, vendor-neutral abstraction. Full source ownership. - [GPT-5.6 (Sol, Terra, Luna): Pricing, Benchmarks, and What It Changes](https://www.kensink.com/models/openai-gpt/gpt-5-6.md): A senior lab's read on OpenAI GPT-5.6: the Sol / Terra / Luna suite, pricing, benchmarks vs GPT-5.5, Claude Opus 4.8 and Gemini 3.1 Pro, the new caching model... - [Speech-to-Text & Whisper Services: Kensink Labs](https://www.kensink.com/models/whisper-speech.md): Production transcription from a senior lab: Whisper, diarization, timestamps, wired into your LLM pipeline. Full source ownership. ## LLM engineering - [Direct LLM Engineering: Eight services on the K-Framework](https://www.kensink.com/llm.md): Senior engineers shipping direct-LLM systems. No LangChain, no LlamaIndex, no framework lock-in. - [Production LLM Agents: typed tools, guardrails, traces](https://www.kensink.com/llm/agents.md): Tool-using agents with schema-validated function calling, bounded retry budgets, per-tool rate limits, OpenTelemetry traces. - [Enterprise LLM Deployment: SSO, RBAC, audit, PII](https://www.kensink.com/llm/enterprise.md): Production LLM for regulated industries. SSO + RBAC + audit trails + PII redaction enforced at the proxy. Vendor-neutral abstraction. - [LLM Model Evaluation: golden sets, hard assertions, drift detection](https://www.kensink.com/llm/evaluation.md): Eval-first LLM development. Golden sets, CI gates, LLM-as-judge soft scoring, production drift detection. - [Fine-tuning · LoRA, DPO, GRPO, custom models](https://www.kensink.com/llm/fine-tuning.md): Enterprise fine-tuning hub: LoRA / QLoRA / DoRA / full SFT, preference optimization (DPO, SimPO, ORPO, KTO), reinforcement fine-tuning (GRPO/RFT), continued... - [Fine-tuning by data + compute scale: four named playbooks](https://www.kensink.com/llm/fine-tuning/by-scale.md): From under 1k examples to over 1M. Single A10G to 128 B200. Indicative cost, recommended method, hardware tier per scale. - [Fine-tuning compliance: EU AI Act, GDPR, HIPAA, Colorado AI Act, DPDP, China GenAI](https://www.kensink.com/llm/fine-tuning/compliance.md): Region-by-region compliance for fine-tuned LLMs. EU AI Act (Article 25 substantial modification, GPAI training-data summary), GDPR Article 17 erasure, US state... - [Custom model build: CPT, SFT, DPO, reasoning distillation, merging](https://www.kensink.com/llm/fine-tuning/custom-models.md): Build a custom enterprise LLM from a frontier-grade open base. Continued pretraining, SFT, preference optimization (DPO / SimPO / ORPO), R1-style reasoning... - [Fine-tuning data pipeline: sourcing, PII, synthetic, dedup, labelling](https://www.kensink.com/llm/fine-tuning/data-pipeline.md): The data engineering depth for enterprise fine-tuning. Sourcing strategies, PII redaction (Presidio), synthetic data (Distilabel, Nemotron), DEITA quality... - [Fine-tuning methods: LoRA, QLoRA, SFT, DPO, GRPO, DoRA](https://www.kensink.com/llm/fine-tuning/methods.md): Every named fine-tuning technique with engineering depth: LoRA, QLoRA, DoRA, full SFT, DPO, SimPO, ORPO, KTO, GRPO/RFT, continued pretraining, distillation... - [Continued pretraining (CPT) for LLMs: domain-adaptive pretraining](https://www.kensink.com/llm/fine-tuning/methods/cpt.md): Continued pretraining for foreign vocabulary, new tokenization, and deep domain language. When SFT cannot fix what the base never saw. - [LLM distillation: small students from frontier teachers](https://www.kensink.com/llm/fine-tuning/methods/distillation.md): Reasoning distillation (R1 lineage), output distillation, custom-model distillation pipelines. The 2025 breakout method for cheap, fast specialist models. - [DoRA fine-tuning: weight-decomposed LoRA](https://www.kensink.com/llm/fine-tuning/methods/dora.md): DoRA decomposes weights into magnitude and direction. Up to +4.4% over LoRA at the same trainable parameter count. Drop-in replacement in PEFT and Unsloth. - [DPO fine-tuning: direct preference optimization](https://www.kensink.com/llm/fine-tuning/methods/dpo.md): Direct Preference Optimization for alignment without the PPO loop. Reference SFT, preference pairs, classification loss. The 2026 production workhorse. - [GRPO / Reinforcement Fine-Tuning: reasoning fine-tunes for LLMs](https://www.kensink.com/llm/fine-tuning/methods/grpo-rft.md): Group Relative Policy Optimization (DeepSeek R1) and OpenAI's RFT API for verifiable-reward fine-tuning. Math, code, structured extraction, tool use. - [KTO fine-tuning: preference learning from thumbs](https://www.kensink.com/llm/fine-tuning/methods/kto.md): Kahneman-Tversky Optimization trains on single-response binary labels. The right method when production feedback is thumbs, not pairwise comparisons. - [LoRA fine-tuning: the 2026 default, by Kensink Labs](https://www.kensink.com/llm/fine-tuning/methods/lora.md): Low-rank adaptation: 99% of the accuracy of a full fine-tune, 1% of the VRAM. Rank 16, alpha 32, all-linear is our 2026 default. - [LLM model merging: TIES, DARE, model soup](https://www.kensink.com/llm/fine-tuning/methods/model-merging.md): Combine fine-tunes by weight arithmetic. TIES, DARE, SLERP, task arithmetic. Multi-skill consolidation in minutes, no GPU training needed. - [ORPO fine-tuning: one-stage SFT + preference](https://www.kensink.com/llm/fine-tuning/methods/orpo.md): Odds-Ratio Preference Optimization merges SFT and preference learning into one run. Half the compute of SFT then DPO, close quality on clean data. - [QLoRA fine-tuning: 4-bit base + LoRA on a single GPU](https://www.kensink.com/llm/fine-tuning/methods/qlora.md): QLoRA enables Llama 70B fine-tuning on a single 48GB GPU. NF4 + double-quantization + paged 8-bit AdamW. Our default when VRAM is the budget you do not have. - [Full SFT fine-tuning: when LoRA falls short](https://www.kensink.com/llm/fine-tuning/methods/sft.md): Full supervised fine-tuning: every weight updates. The highest accuracy ceiling, the highest cost. When we benchmark past LoRA and full SFT earns the build. - [SimPO fine-tuning: reference-free preference optimization](https://www.kensink.com/llm/fine-tuning/methods/simpo.md): SimPO drops the reference model and adds length normalization. +6.4 AlpacaEval 2 and +7.5 Arena-Hard over DPO at lower training memory. - [Fine-tuning platforms: OpenAI RFT, Anthropic, Vertex, Bedrock, Together, Predibase, NeMo](https://www.kensink.com/llm/fine-tuning/platforms.md): Side-by-side of the 12 platforms that matter for production fine-tuning: OpenAI RFT, Anthropic on Bedrock, Vertex AI, Azure Foundry, Databricks Mosaic, Together... - [LLM Observability & Cost: telemetry, drift, caps](https://www.kensink.com/llm/observability.md): Token + cost telemetry per user, per endpoint, per prompt version. Drift detection on production traffic. Per-tenant caps with graceful degradation. - [On-Premise LLM Deployment: vLLM + Triton + your VPC](https://www.kensink.com/llm/on-premise.md): Self-hosted inference on Llama, Mistral, Qwen. vLLM + Triton + Kubernetes. GPU sizing, autoscaling, air-gapped where required. - [RAG · Production Retrieval-Augmented Generation](https://www.kensink.com/llm/rag.md): Hub for production RAG: architectures (Naive, Advanced, Agentic, GraphRAG), vector databases (pgvector, Qdrant, Milvus, Vespa), retrieval pipeline (embeddings... - [RAG Architectures: Sketched, Benchmarked, Ranked by When Each Ships](https://www.kensink.com/llm/rag/architectures.md): Every published RAG pattern in production engineering use. Architecture sketches, eval methodology, deployment notes, and an honest verdict on when each one... - [Adaptive RAG: Per-Query Routing for Cost Optimisation](https://www.kensink.com/llm/rag/architectures/adaptive.md): Adaptive RAG routes each query to the cheapest mode that can handle it. Classifier + multiple RAG modes. The 2026 production cost-optimisation pattern. - [Advanced RAG (Hybrid + Rerank): Stack, Deploy, Benchmarks](https://www.kensink.com/llm/rag/architectures/advanced.md): Production Advanced RAG: query rewrite, hybrid (pgvector + BM25) retrieval, reciprocal-rank fusion, cross-encoder rerank, citation-first generation. - [Agentic RAG: Production Patterns, Stack, Cost Control](https://www.kensink.com/llm/rag/architectures/agentic.md): Agentic RAG in production: planner + per-source retrievers + validator + synthesizer with hard budget and structured output. - [Branched RAG: Parallel Hypothesis Exploration](https://www.kensink.com/llm/rag/architectures/branched.md): Branched RAG: generate multiple interpretations, retrieve in parallel, compare and synthesize. For open-ended questions where multiple angles deserve answers. - [Corrective RAG (CRAG): Retrieval Eval + Web Fallback](https://www.kensink.com/llm/rag/architectures/corrective.md): Production CRAG: lightweight retrieval evaluator + web-search fallback when documents are weak. Catches bad retrievals before they bleed through. - [GraphRAG: Multi-Hop Knowledge Graph Retrieval](https://www.kensink.com/llm/rag/architectures/graphrag.md): Production GraphRAG: entity + relationship extraction, knowledge graph build, community detection, graph traversal, path-aware synthesis. - [HyDE: Hypothetical Document Embeddings for Technical RAG](https://www.kensink.com/llm/rag/architectures/hyde.md): HyDE: have the LLM write a hypothetical answer, embed it, find real documents that match. Lifts recall on technical and jargon-heavy queries. - [Iterative RAG: Multi-Round Retrieval for Research Workloads](https://www.kensink.com/llm/rag/architectures/iterative.md): Iterative RAG: retrieve, partial answer, identify gap, refine, repeat. The pattern for research questions that decompose into sub-questions. - [Modular RAG: Swappable Components for Production Builds](https://www.kensink.com/llm/rag/architectures/modular.md): Modular RAG: named modules with typed contracts, swappable components, no framework lock-in. - [Naive RAG: The Baseline Every RAG Build Starts From](https://www.kensink.com/llm/rag/architectures/naive.md): Naive RAG explained: embed, fetch top-K, generate. The fastest thing that works, the baseline every more complex pattern earns its way past. - [Self-RAG: Self-Critique RAG for High-Stakes Accuracy](https://www.kensink.com/llm/rag/architectures/self-rag.md): Production Self-RAG: retrieval critique + answer critique + calibrated refusal. Catches confident wrong answers in clinical, legal, financial, regulatory work. - [RAG with Memory: Conversational Context for Production Chat](https://www.kensink.com/llm/rag/architectures/simple-with-memory.md): RAG plus conversation buffer for multi-turn chat. Pronouns resolve, follow-ups work, retention controls. Stack, deploy, privacy posture, our take. - [Speculative RAG: Pre-Fetch Likely Follow-Ups](https://www.kensink.com/llm/rag/architectures/speculative.md): Speculative RAG anticipates follow-up queries and pre-fetches retrieval in the background. Cuts perceived latency on conversational workloads. - [RAG by corpus scale: proven designs from <100k to 1B+ chunks](https://www.kensink.com/llm/rag/by-scale.md): Four named RAG architectures by corpus size: under 100k chunks (pgvector + hybrid), 100k-10M (Qdrant + rerank), 10M-1B (Milvus / Vespa multi-stage), 1B+... - [Multimodal RAG: PDFs with tables, vision LLMs, ColPali, BGE-M3](https://www.kensink.com/llm/rag/multimodal.md): Multimodal RAG for documents that aren't plain text. Vision LLM extraction (Claude, GPT), multimodal embeddings (ColPali, BGE-M3), table-aware chunking... - [RAG retrieval pipeline: embeddings, chunking, hybrid search, reranking](https://www.kensink.com/llm/rag/retrieval-pipeline.md): The four layers retrieval quality lives in: embedding model selection, chunking strategies (late chunking, contextual retrieval), hybrid search (vector + BM25 +... - [Vector databases for RAG: pgvector, Qdrant, Milvus, Weaviate, Vespa, LanceDB, Pinecone](https://www.kensink.com/llm/rag/vector-databases.md): Honest 2026 comparison of the seven vector databases that matter for production RAG. Selection matrix by corpus scale, hybrid native, latency, and ops cost. - [LLM Structured Output: Zod schemas, validator loops](https://www.kensink.com/llm/structured-output.md): JSON schema enforcement on LLM output. Zod schemas mirror the API contract. Validator loops with bounded retries and repair prompts. Type-safe end-to-end. ## Founder hub - [Kensink Labs Founders AI · Build your AI business with a lab that ships](https://www.kensink.com/founder.md): Your AI co-founder for the build. Scan your idea for free, then ship it with a ready-made engineering, marketing, or content team. - [Content Lab for founders](https://www.kensink.com/founder/content.md): A ready-made content crew for blog, docs, and long-form. A founder narrative people remember, content that teaches and ranks, and a publishing rhythm you can... - [AI Engineering Team for founders](https://www.kensink.com/founder/engineering.md): A ready-made engineering crew that builds, tests, and ships your AI product. MVPs, AI agents, and a codebase your future team can maintain. - [AI Marketing Team for founders](https://www.kensink.com/founder/marketing.md): A ready-made marketing crew that plans the launch, writes the copy, and reads the numbers. - [Founder pricing](https://www.kensink.com/founder/pricing.md): A ladder built for founders. Start with a free AI readiness teardown, then a fixed-scope Launch Sprint, an embedded team, or full scale. - [AI Readiness Scanner](https://www.kensink.com/founder/readiness.md): Score your AI product idea in two minutes. See what is AI-ready, what is not, how to close the gap, and a roadmap to launch. Free, no sign-up to see your score. - [Founder resources](https://www.kensink.com/founder/resources.md): Playbooks for building with AI: idea to MVP in a few weeks, an AI stack for a pre-seed startup, and when to hire versus when to embed. - [An AI stack for a pre-seed startup](https://www.kensink.com/founder/resources/an-ai-stack-for-a-pre-seed-startup.md): The boring, cheap, scalable stack we reach for when a founder has no infra and no time to manage it. - [Idea to MVP in a few weeks](https://www.kensink.com/founder/resources/idea-to-mvp-in-a-few-weeks.md): How to scope an AI product down to the smallest thing worth shipping, and ship it before the idea goes stale. - [When to hire vs when to embed](https://www.kensink.com/founder/resources/when-to-hire-vs-when-to-embed.md): A simple test for whether you should hire an AI team now, or embed one until you have traction. ## Industries - [Industries: production AI by vertical](https://www.kensink.com/industries.md): Five industry verticals, six service items each, all built on the K-Framework. Recruiting AI, healthcare AI, fintech AI, manufacturing AI, edtech AI. - [Accounting AI: invoicing, reconciliation, close-ready books](https://www.kensink.com/industries/accounting-ai.md): Production AI for SME finance. Invoicing that chases itself, continuous reconciliation, and a close-ready ledger. - [Agritech AI: farmer marketplaces, identity, native language](https://www.kensink.com/industries/agritech-ai.md): Production agritech platforms built the way farmers work. Storefronts, public markets, farmer identity, and B2B networks, delivered natively in the local... - [EdTech AI: teach-back, voice, kid-safe tutoring](https://www.kensink.com/industries/edtech-ai.md): Production AI for K-12 platforms, after-school tutoring apps, and university copilots. Teach-back loops, voice-first STT/TTS, kid-safe guardrails, and a parent... - [Fintech AI: fraud, KYC, audit-grade observability](https://www.kensink.com/industries/fintech-ai.md): Production AI for neobanks, payment platforms, lending, and regulated fintech. Fraud detection, KYC document AI, audit-grade observability, and on-prem... - [Healthcare AI: clinical summarization, evals, audit](https://www.kensink.com/industries/healthcare-ai.md): Production AI for hospitals, EHR add-ons, and clinical platforms. Clinical summarization, evidence-grounded copilots, on-prem deployment, and HIPAA-aware audit... - [Manufacturing AI: predictive maintenance, vision, edge](https://www.kensink.com/industries/manufacturing-ai.md): Production AI for manufacturers and supply-chain operators. Predictive maintenance, vision defect detection, OT/IT bridge, and edge inference that survives 24/7... - [Membership & Education AI: from answering to running the business](https://www.kensink.com/industries/membership-ai.md): Production AI for online academies, membership communities, and creator-educators. A grounded, multilingual agent that converts demand and serves members, built... - [Recruiting AI: production matching, evals, copilots](https://www.kensink.com/industries/recruiting-ai.md): AI matching for platforms that move millions of people into work. Vector retrieval, eval suites, multilingual career copilots, and the boring infrastructure... ## K-Framework - [The K-Framework: A layered map of AI development](https://www.kensink.com/k-framework.md): Kensink Labs' operating system for shipping AI products that survive production. Three pillars, sixteen layers, one feedback loop. - [Algorithmic Fundamentals: K-Framework Layer A.03](https://www.kensink.com/k-framework/algorithmic-fundamentals.md): Validate the Algorithmic Fundamentals layer: defensible retrieval, rerank, and decoding choices recorded in ADRs, and a pipeline you can debug stage by stage. - [Architectural Visibility: K-Framework Layer C.02](https://www.kensink.com/k-framework/architectural-visibility.md): Validate the Architectural Visibility layer: architecture-as-code, current service catalogs and data-flow maps, ADRs, and diagrams used in reviews. - [Automated Rollback: K-Framework Layer B.05](https://www.kensink.com/k-framework/automated-rollback.md): Validate the Automated Rollback layer: gradual rollout, reversible migrations validated in CI, feature flags, and a rehearsed rollback. - [Automation Layer: K-Framework Layer B.02](https://www.kensink.com/k-framework/automation-layer.md): Validate the Automation Layer: PR-driven deploys, runbooks as code, parity staging, and synthetic monitoring of the user journey. A CEO/CTO field guide. - [Code as Liability: K-Framework Layer A.05](https://www.kensink.com/k-framework/code-as-liability.md): Validate the Code as Liability layer: tests that gate merges, strict types, ADRs on non-trivial changes, and a codebase your team can extend without rewriting. - [Critical Thinking: K-Framework Layer C.03](https://www.kensink.com/k-framework/critical-thinking.md): Validate the Critical Thinking layer: reviews that re-derive assumptions, inherited defaults challenged, and a team that can defend every key choice. - [Data Strategy: K-Framework Layer A.02](https://www.kensink.com/k-framework/data-strategy.md): Validate the Data Strategy layer of an AI system: contract-first data, lineage from source to retrieval, schema-level PII gating, and reviewed retention. - [Ethics & Safety: K-Framework Layer A.04](https://www.kensink.com/k-framework/ethics-safety.md): Validate the Ethics & Safety layer: safety evals that gate releases, red-team prompts in CI, PII detection on inputs and outputs, and pre-release InfoSec... - [Evaluation Engine: K-Framework Layer B.03](https://www.kensink.com/k-framework/evaluation-engine.md): Validate the Evaluation Engine: an eval suite written before the feature, gated on every PR, with per-field scoring and a red-team set. - [Intellectual Ownership: K-Framework Layer C.04](https://www.kensink.com/k-framework/intellectual-ownership.md): Validate the Intellectual Ownership layer: ADRs that name the decider and reasoning, a questioner in reviews, and decision-focused post-incident reviews. - [Long-Term Vision: K-Framework Layer A.06](https://www.kensink.com/k-framework/long-term-vision.md): Validate the Long-Term Vision layer: direct-to-model choices, durable infrastructure, named long-horizon constraints, and a standing architecture review. - [Mentorship Speed-Run: K-Framework Layer C.01](https://www.kensink.com/k-framework/mentorship-speed-run.md): Validate the Mentorship Speed-Run layer: pair-engineering by default, co-authored decisions, and a team that can defend and extend the system at handoff. - [Model & Tooling: K-Framework Layer B.01](https://www.kensink.com/k-framework/model-tooling.md): Validate the Model & Tooling layer: tool selection as a scored decision doc, direct-to-model by default, and a known exit path for every dependency. - [System Design: K-Framework Layer A.01](https://www.kensink.com/k-framework/system-design.md): How to validate the System Design layer of an AI build: reference architecture signed off before code, a failure mode per component, and NFRs gated in CI. - [Token Economics: K-Framework Layer B.04](https://www.kensink.com/k-framework/token-economics.md): Validate the Token Economics layer: cost-per-intent metering, per-customer budgets, regression alerts on PRs, and a quarterly model-cost review. - [Values & Purpose: K-Framework Layer C.05](https://www.kensink.com/k-framework/values-purpose.md): Validate the Values & Purpose layer: a charter naming user, moment, and outcome, re-read weekly and used to gate what ships. A CEO/CTO field guide. ## More - [Kensink Labs: AI products on solid ground](https://www.kensink.com/_not-found.md): A small lab of senior engineers shipping production AI for SaaS companies. no framework lock-in. - [Kensink Labs: AI products on solid ground](https://www.kensink.com/404.md): A small lab of senior engineers shipping production AI for SaaS companies. no framework lock-in. - [About](https://www.kensink.com/about.md): A small lab of senior engineers shipping production AI. Founded by Niaz Islam. New York, est. 2024. - [Ad Optimization](https://www.kensink.com/ad-optimization.md): Most businesses waste 70% of their ad budget. Simple fixes that double your results without increasing your spend. - [AI Agents](https://www.kensink.com/ai-agents.md): Stop debugging frameworks built on quicksand. We engineer production-ready AI agents on a rock-solid foundation. - [Contact](https://www.kensink.com/contact.md): Get in touch. Send a message or book a 15-min intro call. We reply within 24 hours. - [Design System v2](https://www.kensink.com/design-system.md): Internal visual manual for Kensink Labs. Tokens, components, and rules that ship from src/components/ui. - [Dispatch: Field notes from Kensink Labs](https://www.kensink.com/dispatch.md): A lab dispatch from Kensink Labs. Engineering notes, half-finished diagrams, and the occasional rant about file formats. - [Engagements: services with a spec you can read](https://www.kensink.com/engagements.md): Fixed-scope service engagements with a real spec: the offer, what is in and out of scope, the deliverables, the timeline, and the SLA. - [AI Agents engagement: scope, deliverables, SLA](https://www.kensink.com/engagements/ai-agents.md): A fixed-scope AI agents engagement, eval-gated before it ships. Full spec: offer, in and out of scope, deliverables, an eight-week timeline, and the SLA it runs... - [Frontier Firm engagement: scope, deliverables, SLA](https://www.kensink.com/engagements/frontier-firm.md): A twelve-week program to restructure one function around AI agents, with a working system and a repeatable playbook. - [LLM Apps engagement: RAG, evals, SLA](https://www.kensink.com/engagements/llm-apps.md): A fixed-scope LLM app engagement: retrieval, evaluation, and cost control for a feature that holds up in production. - [Mobile Apps engagement: scope, deliverables, SLA](https://www.kensink.com/engagements/mobile-apps.md): A fixed-scope mobile engagement: a cross-platform app shipped to both stores, with a release pipeline your team owns. - [MVP Development engagement: scope, deliverables, SLA](https://www.kensink.com/engagements/mvp.md): A fixed-scope MVP engagement: idea to a validated build in four to six weeks, on a foundation that extends into a product. - [Website Audit engagement: scope, deliverables, SLA](https://www.kensink.com/engagements/website-audit.md): A one-week website audit across performance, AI-readiness, and conversion, with a ranked fix list. Full spec with scope, deliverables, timeline, and SLA. - [Enterprise Software Development](https://www.kensink.com/enterprise.md): Custom enterprise software built by senior engineers. Direct integration, eval-first, full source ownership. - [Expertise](https://www.kensink.com/expertise.md): Boring infrastructure, modern AI. Direct LLM integration, Postgres, pgvector, eval-first development. Six platforms, ten industries. - [Frontier Firm Transformation](https://www.kensink.com/frontier-firm.md): We don't just build AI companies. We are one. The 12-week organizational transformation around AI: the work chart, the agent boss, the unit economics, and the... - [Guides](https://www.kensink.com/guides.md): Practical guides to the Kensink Builders Lab. Start with the white-label Partner Portal: branding, the proposal builder, costing, and the client experience. - [Partner Portal guides](https://www.kensink.com/guides/partner-portal.md): Run your own white-label proposals on the Kensink Builders Lab. Your logo, your colours, your domain, your Stripe. Your clients never see Kensink. - [What your client sees. · Partner Portal](https://www.kensink.com/guides/partner-portal/client-experience.md): The three-tab client view: a live Experience mock, the written Proposal, and a Costing tab with the decision and checkout, all in your brand. - [The Partner Portal, end to end. · Partner Portal](https://www.kensink.com/guides/partner-portal/overview.md): What the partner portal is, the two surfaces you work in, and exactly what each one lets you do, with no Kensink visible to your clients. - [Set up your partner workspace. · Partner Portal](https://www.kensink.com/guides/partner-portal/setup.md): Everything that makes a workspace yours: brand, custom domain, sending email, Slack alerts, Stripe payouts, AI voice, and team access. - [Languages & Frameworks We Build In: Kensink Labs](https://www.kensink.com/languages.md): The languages and frameworks Kensink Labs builds production software in: React, Next.js, TypeScript, Python, React Native, Flutter, and more. - [Django Development Services: Kensink Labs](https://www.kensink.com/languages/django.md): Django builds from a senior lab: clean app structure, typed Python, eval-tested, full source ownership at handoff. - [FastAPI Development Services: Kensink Labs](https://www.kensink.com/languages/fastapi.md): Typed Python APIs with FastAPI: automatic OpenAPI, async performance, eval-tested AI integration, full source ownership. - [Flutter Development Services: Kensink Labs](https://www.kensink.com/languages/flutter.md): Flutter apps with pixel-identical UI across platforms. Senior engineers, eval-tested, full source ownership at handoff. - [Go (Golang) Development Services: Kensink Labs](https://www.kensink.com/languages/golang.md): Fast, concurrent Go services and infrastructure from a senior lab. Eval-tested, full source ownership at handoff. - [Android Development Services (Kotlin): Kensink Labs](https://www.kensink.com/languages/kotlin-android.md): Native Android with Kotlin and Jetpack Compose. Senior engineers, eval-tested, full source ownership at handoff. - [Laravel / PHP Development Services: Kensink Labs](https://www.kensink.com/languages/laravel-php.md): Laravel and PHP builds from a senior lab: clean structure, tested, full source ownership at handoff. - [Next.js Development Services: Kensink Labs](https://www.kensink.com/languages/nextjs.md): Next.js App Router builds from a senior lab: server components, edge rendering, strong SEO, full source ownership. Problem to production in eight weeks. - [Node.js Development Services: Kensink Labs](https://www.kensink.com/languages/nodejs.md): TypeScript-first Node.js backends from a senior lab. Small dependency surface, eval-tested, full source ownership. - [Python Development Services: Kensink Labs](https://www.kensink.com/languages/python.md): Typed, tested Python for backends, data pipelines, and AI tooling. Senior engineers, eval-first, full source ownership at handoff. - [React Native Development Services: Kensink Labs](https://www.kensink.com/languages/react-native.md): Cross-platform iOS and Android with React Native and Expo. Shared logic with web, eval-tested, full source ownership. - [React Development Services: Kensink Labs](https://www.kensink.com/languages/react.md): Typed, server-first React from a senior lab. Maintainable component systems, eval-tested, with full source ownership at handoff. - [iOS Development Services (Swift): Kensink Labs](https://www.kensink.com/languages/swift-ios.md): Native iOS with Swift and SwiftUI. Senior engineers, deep platform integration, eval-tested, full source ownership. - [TypeScript Development Services: Kensink Labs](https://www.kensink.com/languages/typescript.md): Strict, end-to-end TypeScript from a senior lab. Shared contracts across the stack, eval-tested, full source ownership. - [Vue.js Development Services: Kensink Labs](https://www.kensink.com/languages/vuejs.md): Typed, tested Vue.js from a senior lab. Maintainable apps, eval-tested, full source ownership at handoff. - [Mobile App Development](https://www.kensink.com/mobile-app.md): Ship mobile apps you can maintain. Senior engineers, app-store hardened, full source ownership at handoff. - [MVP Development](https://www.kensink.com/mvp.md): Ship your MVP in eight weeks. User-validated features only. Built for scale from day one. Full source code ownership. - [Application Design Patterns: Kensink Labs](https://www.kensink.com/patterns.md): Architecture patterns Kensink Labs builds with: RAG, multi-agent systems, event-driven, microservices, serverless, multi-tenant SaaS, CQRS, and headless. - [CQRS & Event Sourcing: Kensink Labs](https://www.kensink.com/patterns/cqrs-event-sourcing.md): CQRS and event sourcing from a senior lab: auditability and domain clarity, applied where it earns its complexity. Full source ownership. - [Event-driven Architecture: Kensink Labs](https://www.kensink.com/patterns/event-driven.md): Event-driven systems from a senior lab: queues, idempotency, observability, applied where decoupling pays. Full source ownership. - [Headless & API-first Architecture: Kensink Labs](https://www.kensink.com/patterns/headless-api-first.md): API-first and headless architecture from a senior lab: versioned contracts, OpenAPI, multi-client. Full source ownership. - [Microservices Architecture: Kensink Labs](https://www.kensink.com/patterns/microservices.md): Microservices from a senior lab: boundaries drawn for real needs, honest about monoliths. Eval-tested, full source ownership. - [Multi-tenant SaaS Architecture: Kensink Labs](https://www.kensink.com/patterns/multi-tenant-saas.md): Multi-tenant SaaS architecture from a senior lab: isolation models, data-layer enforcement, tested boundaries. Full source ownership. - [Serverless Architecture: Kensink Labs](https://www.kensink.com/patterns/serverless.md): Serverless architecture from a senior lab: scale-to-zero, edge-first, designed around the limits. Full source ownership. - [Privacy Policy](https://www.kensink.com/privacy.md): How Kensink Labs collects, stores, and uses information from website visitors and clients. - [Market-ready products](https://www.kensink.com/products.md): Products you can adopt today, not just bespoke builds: an AI receptionist, an API observability platform, a skills and model marketplace, and the platform we... - [AI Coach: Skills and Model Marketplace](https://www.kensink.com/products/ai-coach.md): AI Coach is a marketplace of vetted AI skills and MCP tools with honest model comparisons and bakeoffs, so teams install the right capability on the right... - [AI Receptionist: Kensink Labs](https://www.kensink.com/products/ai-receptionist.md): An AI receptionist that answers every call and message, books appointments, and qualifies leads twenty-four hours a day, in your business's voice. - [Builders Lab: Partner Operating System](https://www.kensink.com/products/builders-lab.md): Builders Lab is the platform behind Kensink delivery, opened to partners: CRM, licensing and settlement, white-label storefronts, custom domains, and email on... - [NuForce AI: Invoicing and Accounting AI for SMEs](https://www.kensink.com/products/nuforce-ai.md): NuForce AI is a business AI for SME finance. It raises and chases invoices, reconciles accounts, and keeps the books close-ready, so small teams run finance... - [Omazy CX: Enterprise Customer Experience Platform](https://www.kensink.com/products/omazy-cx.md): Omazy CX unifies customer touchpoints, agent support, and post-purchase recovery on one platform. - [OpenAPI Studio: API Observability Platform](https://www.kensink.com/products/openapi-studio.md): OpenAPI Studio gives engineering teams end-to-end API visibility: security posture, runtime observability, and contract testing, with the OpenAPI spec as the... - [OU.Chat: Sovereign, Private Enterprise AI](https://www.kensink.com/products/ou-chat.md): OU.Chat is a white-label enterprise AI app that runs on your own models and data. No prompts leave your boundary for OpenAI or Google. - [AI ROI Calculator](https://www.kensink.com/resources/ai-roi-calculator.md): Estimate the payback on a direct-LLM agent project before committing budget. Five inputs, live output, methodology footnoted. - [Frontier Firm Diagnostic](https://www.kensink.com/resources/frontier-diagnostic.md): Twelve-question diagnostic. Score your readiness to become a Frontier Firm across leadership, tech, process, and talent. - [The Frontier Firm Playbook](https://www.kensink.com/resources/frontier-playbook.md): A 20-page field guide to the 12-week organizational AI transformation. Free download. - [Direct LLM Integration Guide](https://www.kensink.com/resources/llm-integration-guide.md): A 15-page engineering guide to integrating directly with the LLM API. No frameworks. - [What We Build, Project Types: Kensink Labs](https://www.kensink.com/services.md): The kinds of software Kensink Labs builds: web applications, marketing sites, SaaS products, e-commerce, APIs, internal tools, mobile, and enterprise systems. - [API & Backend Development: Kensink Labs](https://www.kensink.com/services/api-backend-development.md): API and backend development from a senior lab: API-first design, typed, tested, observable. Full source ownership at handoff. - [E-commerce Development: Kensink Labs](https://www.kensink.com/services/ecommerce-development.md): Custom e-commerce from a senior lab: storefront, checkout, reconciling payments, headless where it helps. Full source ownership. - [Internal Tools & Dashboards: Kensink Labs](https://www.kensink.com/services/internal-tools-dashboards.md): Internal tools and dashboards from a senior lab: real auth, audit, and usable UI to retire the spreadsheet. Full source ownership. - [Marketing Website Development: Kensink Labs](https://www.kensink.com/services/marketing-website.md): Fast, SEO-strong marketing sites from a senior lab: Next.js, server-rendered, conversion-focused. Full source ownership. - [SaaS Product Development: Kensink Labs](https://www.kensink.com/services/saas-product-development.md): SaaS product development from a senior lab: multi-tenancy, billing, auth, and roles built in from day one. Full source ownership in eight weeks. - [Web Application Development: Kensink Labs](https://www.kensink.com/services/web-application-development.md): Custom web application development from a senior lab: Next.js, TypeScript, Postgres, eval-tested, full source ownership in eight weeks. - [Technologies & Infrastructure: Kensink Labs](https://www.kensink.com/technologies.md): The data, infrastructure, and integration technologies Kensink Labs builds on: PostgreSQL, pgvector, Cloudflare, AWS, Redis, Stripe, and more. - [AWS Development Services: Kensink Labs](https://www.kensink.com/technologies/aws.md): Right-sized AWS architecture from a senior lab: infrastructure as code, cost visibility, no service sprawl. Full source ownership. - [Cloudflare OS Explained: Architecture, Gatekeepers, Gadgets](https://www.kensink.com/technologies/cloudflare-os.md): A senior lab's technical guide to Cloudflare OS: the agent workspace, Gadgets on Dynamic Workers, the Gatekeeper security model, taint tracking, the full... - [Cloudflare Workers Development Services: Kensink Labs](https://www.kensink.com/technologies/cloudflare-workers.md): Full-stack apps on Cloudflare Workers, D1, R2, KV, and Durable Objects. Edge-first design from a lab that has shipped it. Full source ownership. - [Docker & Kubernetes Services: Kensink Labs](https://www.kensink.com/technologies/docker-kubernetes.md): Reproducible Docker builds and right-sized Kubernetes from a senior lab. No accidental complexity, full source ownership. - [Search & Elasticsearch Development: Kensink Labs](https://www.kensink.com/technologies/elasticsearch-search.md): Relevant, fast search from a senior lab: Elasticsearch or Postgres full-text, right-sized to your data. Full source ownership. - [GraphQL Development Services: Kensink Labs](https://www.kensink.com/technologies/graphql.md): Typed GraphQL APIs from a senior lab: schema design, caching, N+1 handling, full source ownership at handoff. - [The Agent Harness, Explained: Hermes, OpenClaw, qm: Kensink Labs](https://www.kensink.com/technologies/harness.md): A field guide to the AI agent harness: the agentic loop, the eight layers of the stack, and a deep read on Hermes, OpenClaw, and Y Combinator's qm. - [pgvector & Vector Search: Kensink Labs](https://www.kensink.com/technologies/pgvector.md): Vector similarity search in PostgreSQL with pgvector. Simpler RAG architecture from a senior lab, eval-tested, full source ownership. - [PostgreSQL Development Services: Kensink Labs](https://www.kensink.com/technologies/postgresql.md): PostgreSQL schema design, search, and vectors from a senior lab. Tested migrations, observability, full source ownership at handoff. - [Redis: The In-Memory Data Platform, Explained: Kensink Labs](https://www.kensink.com/technologies/redis.md): An in-depth guide to Redis: data structures, caching patterns, persistence, replication, clustering, and its role in modern AI software. - [Stripe & Payments Integration: Kensink Labs](https://www.kensink.com/technologies/stripe-payments.md): Production payments from a senior lab: idempotent capture, refunds, webhooks, reconciliation, multi-processor abstraction. Full source ownership. - [Real-time & WebSocket Development: Kensink Labs](https://www.kensink.com/technologies/websockets-realtime.md): Real-time features with WebSockets from a senior lab: consistency, reconnection, and scale designed in. Full source ownership. - [Terms of Service](https://www.kensink.com/terms.md): Terms governing engagements with Kensink Labs and use of the kensink.com website. - [Professional Website Audit: Technical, Content, UX, Conversion & AI-Readiness](https://www.kensink.com/website-audit.md): A diagnostic framework, not a checklist. We audit your site across seven dimensions (technical, discovery, content, UX, conversion, analytics, strategy), score... - [AI-Readiness Audit: llms.txt, SSR Parity, Bot Allowlists, Citation Spot-Checks](https://www.kensink.com/website-audit/ai-readiness.md): Most audits are 5 years behind on AI. We audit schema coverage, server-side rendering parity, llms.txt, AI crawler allowlists (GPTBot, ClaudeBot, PerplexityBot... - [Content-Type Audit Rubrics: 13 Page Types, 13 Rubrics](https://www.kensink.com/website-audit/content-types.md): Homepages, pillars, case studies, products, pricing, landing pages, docs, about, contact, legal: each page type fails differently. - [Audit Framework: 14 Sub-Systems Across 7 Dimensions](https://www.kensink.com/website-audit/framework.md): The full diagnostic framework: crawlability, architecture, performance, security, semantic HTML, structured data, AI-readiness, mobile, accessibility, content... - [Audit Process: Prerequisites, 5-Day Cadence, Tooling Stack](https://www.kensink.com/website-audit/process.md): What access we need on day one, the baseline metrics we capture, the exact five-day schedule, and the tooling stack we run.