https://lawzava.com/Field notes on board-level AI execution: operating models, technical leadership, reliability, governance, cost, and infrastructure discipline.Hugoen-usWed, 10 Jun 2026 15:02:12 +0000https://lawzava.com/blog/2026-06-10-decision-latency-p-and-l-variable/Wed, 10 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-10-decision-latency-p-and-l-variable/Decision latency is measurable and should be treated as a direct cost driver.https://lawzava.com/blog/2026-06-10-ai-leadership-bench-roles-interfaces/Wed, 10 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-10-ai-leadership-bench-roles-interfaces/AI scaling needs explicit leadership interfaces between product, platform, reliability, and governance.https://lawzava.com/blog/2026-06-10-operating-cadence-ai-leadership-interfaces/Wed, 10 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-10-operating-cadence-ai-leadership-interfaces/Interfaces describe who owns what. Cadence is what turns those interfaces into compounding output.https://lawzava.com/blog/2026-06-10-post-prototype-ai-org/Wed, 10 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-10-post-prototype-ai-org/Year-two AI failure usually comes from org-design mismatch, not model-quality mismatch. The handoffs are where the system slows down.https://lawzava.com/blog/2026-06-09-ai-vendor-negotiation-playbook/Tue, 09 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-09-ai-vendor-negotiation-playbook/Vendor leverage in AI comes from architecture readiness, eval data, and exit credibility — not procurement theater.https://lawzava.com/blog/2026-06-02-ai-incident-review-changes-architecture/Tue, 02 Jun 2026 00:00:00 +0000https://lawzava.com/blog/2026-06-02-ai-incident-review-changes-architecture/Incident reviews should produce architecture deltas and control updates, not narrative theater.https://lawzava.com/blog/2026-05-28-ai-roadmaps-survive-reality/Thu, 28 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-28-ai-roadmaps-survive-reality/AI roadmaps fail when they are sequenced around ambition instead of dependency, verification, and rollback cost.https://lawzava.com/blog/2026-05-26-hiring-operators-for-ai-teams/Tue, 26 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-26-hiring-operators-for-ai-teams/The highest-leverage AI hires are operators who can handle ambiguity, systems tradeoffs, and verification pressure.https://lawzava.com/blog/2026-05-21-ai-technical-leadership/Thu, 21 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-21-ai-technical-leadership/Technical leadership in mid-2026: anchor decisions in throughput, verification, and operability instead of chasing the latest agent framework.https://lawzava.com/blog/2026-05-19-stop-building-internal-ai-tools-no-one-uses/Tue, 19 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-19-stop-building-internal-ai-tools-no-one-uses/Internal AI tools fail when teams optimize for launch instead of habit formation, trust, and workflow fit.https://lawzava.com/blog/2026-05-14-build-the-system-the-model-cannot-break/Thu, 14 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-14-build-the-system-the-model-cannot-break/A manifesto for building AI-native organizations. Twelve tenets across strategy, architecture, economics, and people — and the only test that matters in year two.https://lawzava.com/blog/2026-05-14-why-ai-platform-teams-become-bottlenecks/Thu, 14 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-14-why-ai-platform-teams-become-bottlenecks/AI platform teams fail when they centralize decisions instead of capabilities. The queue is the bug.https://lawzava.com/blog/2026-05-12-cto-communication-protocol-ai-programs/Tue, 12 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-12-cto-communication-protocol-ai-programs/AI programs fail when each layer hears a different success definition.https://lawzava.com/blog/2026-05-07-ai-governance-without-bureaucracy/Thu, 07 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-07-ai-governance-without-bureaucracy/Effective AI governance is tighter defaults, clearer ownership, and faster escalation — not more committees.https://lawzava.com/blog/2026-05-05-measure-ai-progress-without-theater/Tue, 05 May 2026 00:00:00 +0000https://lawzava.com/blog/2026-05-05-measure-ai-progress-without-theater/Most AI progress reporting confuses activity with value. Executive measurement should collapse around adoption, reliability, margin, and delivery speed.https://lawzava.com/blog/2026-04-30-ai-build-vs-buy/Thu, 30 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-30-ai-build-vs-buy/By mid-2026, AI build vs buy has nothing to do with novelty. It is a ruthless mathematical calculation of telemetry, context freshness, and infrastructure lock-in.https://lawzava.com/blog/2026-04-28-margin-risk-speed-ai-strategy-metrics/Tue, 28 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-28-margin-risk-speed-ai-strategy-metrics/Most AI strategy becomes clearer when leadership stops tracking novelty and starts forcing every decision through three numbers.https://lawzava.com/blog/2026-04-23-ai-evaluation-maturity/Thu, 23 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-23-ai-evaluation-maturity/The gap between stable AI features and shipping chaos isn’t tools—it’s production governance. How mature teams evaluate, deploy, and roll back.https://lawzava.com/blog/2026-04-21-enterprise-ai-architecture-fails/Tue, 21 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-21-enterprise-ai-architecture-fails/In 2026, enterprise AI isn’t failing because models are bad. It is failing because organizations are building brittle demos instead of bounded, operable systems.https://lawzava.com/blog/2026-04-16-ai-capital-allocation-what-to-stop-funding/Thu, 16 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-16-ai-capital-allocation-what-to-stop-funding/Strong AI strategy starts with a kill list. If a project cannot defend margin, risk, or speed, it should not survive the next budget meeting.https://lawzava.com/blog/2026-04-14-ai-cto-perspective/Tue, 14 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-14-ai-cto-perspective/A CTO’s AI strategy is not about chasing models. It is about resilient data infrastructure, operational boundaries, and measured throughput.https://lawzava.com/blog/2026-04-06-sovereign-systems-privacy-non-optional/Mon, 06 Apr 2026 00:00:00 +0000https://lawzava.com/blog/2026-04-06-sovereign-systems-privacy-non-optional/Privacy is an architecture constraint, not a feature toggle. Building sovereignty in early avoids painful retrofits and closes enterprise deals faster.https://lawzava.com/blog/2026-03-30-throughput-engineer-headcount-lagging-metric/Mon, 30 Mar 2026 00:00:00 +0000https://lawzava.com/blog/2026-03-30-throughput-engineer-headcount-lagging-metric/Headcount is a lagging metric. The best engineering organizations measure throughput: decision speed, defect containment, and constraint removal.https://lawzava.com/blog/2026-03-23-agenticops-networking-bottleneck/Mon, 23 Mar 2026 00:00:00 +0000https://lawzava.com/blog/2026-03-23-agenticops-networking-bottleneck/Most AI agent failures are infrastructure failures, not model failures. Legacy networking and missing circuit breakers are the real reliability bottleneck.https://lawzava.com/blog/2026-03-16-de-risking-black-swan-distributed-databases/Mon, 16 Mar 2026 00:00:00 +0000https://lawzava.com/blog/2026-03-16-de-risking-black-swan-distributed-databases/Red-teaming distributed databases before production: most catastrophic failures are compound scenarios nobody practiced, not black swans.https://lawzava.com/blog/2026-03-09-the-end-of-fat-cloud-agentic-economy/Mon, 09 Mar 2026 00:00:00 +0000https://lawzava.com/blog/2026-03-09-the-end-of-fat-cloud-agentic-economy/Local-first, hardware-aware architecture is becoming the default for high-reliability AI: cloud-heavy patterns cost too much and fail unpredictably.https://lawzava.com/blog/2026-03-02-ai-startup-landscape/Mon, 02 Mar 2026 00:00:00 +0000https://lawzava.com/blog/2026-03-02-ai-startup-landscape/By early March 2026, the AI startup market looks less like a gold rush and more like a durable industry. Here’s where leverage sits and what buyers reward.https://lawzava.com/blog/2026-02-23-ai-security-evolution/Mon, 23 Feb 2026 00:00:00 +0000https://lawzava.com/blog/2026-02-23-ai-security-evolution/As of late February 2026, AI security is defined by adaptive attacks and layered, operational defenses.https://lawzava.com/blog/2026-02-16-ai-team-structures/Mon, 16 Feb 2026 00:00:00 +0000https://lawzava.com/blog/2026-02-16-ai-team-structures/A practical guide to central, embedded, and hybrid AI team structures, with roles, tradeoffs, and scaling rules.https://lawzava.com/blog/2026-02-09-ai-cost-trends/Mon, 09 Feb 2026 00:00:00 +0000https://lawzava.com/blog/2026-02-09-ai-cost-trends/AI inference costs are falling, but durable savings come from routing, caching, context control, and cost per outcome.https://lawzava.com/blog/2026-02-02-ai-regulation-reality/Mon, 02 Feb 2026 00:00:00 +0000https://lawzava.com/blog/2026-02-02-ai-regulation-reality/Regulation is already in procurement, security reviews, and internal sign-off. Teams that treat compliance as engineering ship faster than those who bolt it on.https://lawzava.com/blog/2026-01-26-ai-native-architecture-2026/Mon, 26 Jan 2026 00:00:00 +0000https://lawzava.com/blog/2026-01-26-ai-native-architecture-2026/Production AI architecture patterns for gateways, retrieval, evaluation, fallbacks, cost control, and ownership.https://lawzava.com/blog/2026-01-19-ai-agent-reliability/Mon, 19 Jan 2026 00:00:00 +0000https://lawzava.com/blog/2026-01-19-ai-agent-reliability/Reliable agents are engineered, not prompted: bounded tools, validation at every step, explicit recovery paths. Here’s how I build them in Go.https://lawzava.com/blog/2026-01-12-ai-video-applications/Mon, 12 Jan 2026 00:00:00 +0000https://lawzava.com/blog/2026-01-12-ai-video-applications/Video AI is practical for scoped workflows. This post covers what works, how to design for reliability, and where human review still matters.https://lawzava.com/blog/2026-01-05-ai-predictions-2026/Mon, 05 Jan 2026 00:00:00 +0000https://lawzava.com/blog/2026-01-05-ai-predictions-2026/Less hype, more plumbing. Agents get real but stay bounded, routing beats monolithic models, and the winners treat AI like software, not magic.https://lawzava.com/blog/2025-12-22-year-in-review-2025/Mon, 22 Dec 2025 00:00:00 +0000https://lawzava.com/blog/2025-12-22-year-in-review-2025/A year-end look at what actually happened in AI – not the hype, but the operational shift. The novelty phase is over. The infrastructure phase has begun.https://lawzava.com/blog/2025-12-08-ai-2025-reflections/Mon, 08 Dec 2025 00:00:00 +0000https://lawzava.com/blog/2025-12-08-ai-2025-reflections/The most important thing that happened to AI in 2025 wasn’t a model release. It was the shift from ‘what can it do’ to ‘how do we run it.’ That’s progress.https://lawzava.com/blog/2025-11-24-ai-enterprise-scale/Mon, 24 Nov 2025 00:00:00 +0000https://lawzava.com/blog/2025-11-24-ai-enterprise-scale/The pilots work. What fails is going from five demos to fifty production features without an operating model. That’s a management problem, not an AI problem.https://lawzava.com/blog/2025-11-10-ai-incident-management/Mon, 10 Nov 2025 00:00:00 +0000https://lawzava.com/blog/2025-11-10-ai-incident-management/AI systems can return 200 OK while confidently wrong. How to detect, contain, and learn from AI incidents using proven incident response principles.https://lawzava.com/blog/2025-10-27-ai-technical-debt/Mon, 27 Oct 2025 00:00:00 +0000https://lawzava.com/blog/2025-10-27-ai-technical-debt/AI debt hides in prompts nobody owns, evals nobody runs, and data pipelines nobody watches. By the time you notice, every change feels dangerous.https://lawzava.com/blog/2025-10-13-ai-team-productivity/Mon, 13 Oct 2025 00:00:00 +0000https://lawzava.com/blog/2025-10-13-ai-team-productivity/Individual AI speedups are a distraction. The real gains come from treating AI as team infrastructure – embedded in docs, decisions, and onboarding.https://lawzava.com/blog/2025-09-29-ai-roi-measurement/Mon, 29 Sep 2025 00:00:00 +0000https://lawzava.com/blog/2025-09-29-ai-roi-measurement/Most AI ROI calculations are fantasy. Measure honestly: one workflow, full costs, benefits tied to outcomes the business tracks, and a range, not one number.https://lawzava.com/blog/2025-09-15-ai-data-privacy/Mon, 15 Sep 2025 00:00:00 +0000https://lawzava.com/blog/2025-09-15-ai-data-privacy/Privacy in AI systems fails in the details: what gets logged, who can replay prompts, how long artifacts linger. Treat it as infrastructure, not a checkbox.https://lawzava.com/blog/2025-09-01-ai-pair-programming/Mon, 01 Sep 2025 00:00:00 +0000https://lawzava.com/blog/2025-09-01-ai-pair-programming/Treat AI coding assistants like a fast, literal junior dev: tight constraints, critical review, and no expectations of architectural insight.https://lawzava.com/blog/2025-08-18-local-ai-development/Mon, 18 Aug 2025 00:00:00 +0000https://lawzava.com/blog/2025-08-18-local-ai-development/Local AI is no longer a hobby project. How to set it up properly: provider abstraction, versioned models, eval harnesses, and a cloud fallback.https://lawzava.com/blog/2025-08-04-ai-workflow-automation/Mon, 04 Aug 2025 00:00:00 +0000https://lawzava.com/blog/2025-08-04-ai-workflow-automation/The trick to AI workflow automation is simple: let the model decide, let deterministic code act, and never confuse the two.https://lawzava.com/blog/2025-07-21-ai-documentation-systems/Mon, 21 Jul 2025 00:00:00 +0000https://lawzava.com/blog/2025-07-21-ai-documentation-systems/Most AI documentation systems retrieve the wrong version, hallucinate details, and never admit uncertainty. Here’s how to build one that actually helps.https://lawzava.com/blog/2025-07-07-ai-product-metrics/Mon, 07 Jul 2025 00:00:00 +0000https://lawzava.com/blog/2025-07-07-ai-product-metrics/Engagement metrics tell you people clicked. They tell you nothing about whether your AI feature actually helped anyone do anything.https://lawzava.com/blog/2025-06-23-fine-tuning-when-why/Mon, 23 Jun 2025 00:00:00 +0000https://lawzava.com/blog/2025-06-23-fine-tuning-when-why/Fine-tuning is the goto move for teams who skipped the basics. Most of the time, better prompts and proper retrieval solve the actual problem.https://lawzava.com/blog/2025-06-09-ai-customer-support/Mon, 09 Jun 2025 00:00:00 +0000https://lawzava.com/blog/2025-06-09-ai-customer-support/Most AI support systems are built to deflect tickets. The ones that work are built around escalation, grounding, and the idea that customers aren’t idiots.https://lawzava.com/blog/2025-05-26-ai-data-pipelines/Mon, 26 May 2025 00:00:00 +0000https://lawzava.com/blog/2025-05-26-ai-data-pipelines/AI data pipelines are ETL with a retrieval layer bolted on. The discipline is the same as always: detect change, chunk intelligently, keep indexes fresh.https://lawzava.com/blog/2025-05-12-ai-agent-orchestration/Mon, 12 May 2025 00:00:00 +0000https://lawzava.com/blog/2025-05-12-ai-agent-orchestration/Multi-agent systems are distributed systems with the usual coordination headaches. The four patterns I’ve seen work, and when each one falls apart.https://lawzava.com/blog/2025-04-28-ai-security-2025/Mon, 28 Apr 2025 00:00:00 +0000https://lawzava.com/blog/2025-04-28-ai-security-2025/AI systems are exposed APIs with real blast radius. The threats are injection, leakage, and tool misuse. The defenses are the ones we’ve always needed.https://lawzava.com/blog/2025-04-14-ai-testing-production/Mon, 14 Apr 2025 00:00:00 +0000https://lawzava.com/blog/2025-04-14-ai-testing-production/Offline evals are necessary but not sufficient. Here’s how I test AI features in production with shadow mode, canaries, and rollback automation – with Go code.https://lawzava.com/blog/2025-03-31-ai-observability-deep/Mon, 31 Mar 2025 00:00:00 +0000https://lawzava.com/blog/2025-03-31-ai-observability-deep/Traditional monitoring will tell you your AI service is up. It won’t tell you it’s returning confident garbage. Here’s what observability actually looks like for AI.https://lawzava.com/blog/2025-03-17-mcp-model-context-protocol/Mon, 17 Mar 2025 00:00:00 +0000https://lawzava.com/blog/2025-03-17-mcp-model-context-protocol/Model Context Protocol promises to standardize how AI talks to tools. I built an MCP server in Go to see if the promise holds up. Here’s what I found.https://lawzava.com/blog/2025-03-03-ai-governance-practice/Mon, 03 Mar 2025 00:00:00 +0000https://lawzava.com/blog/2025-03-03-ai-governance-practice/Governance that blocks delivery is broken. Governance that makes ‘yes’ safe and fast is a competitive advantage. Here’s how to build the second kind.https://lawzava.com/blog/2025-02-17-video-understanding-ai/Mon, 17 Feb 2025 00:00:00 +0000https://lawzava.com/blog/2025-02-17-video-understanding-ai/I pointed a video understanding pipeline at 200 hours of meeting recordings. The results taught me more about pipeline design than about meetings.https://lawzava.com/blog/2025-02-03-ai-code-review/Mon, 03 Feb 2025 00:00:00 +0000https://lawzava.com/blog/2025-02-03-ai-code-review/I’ve been running AI code review on real PRs for months. It catches some real bugs. It also generates a staggering amount of useless commentary.https://lawzava.com/blog/2025-01-20-reasoning-models-production/Mon, 20 Jan 2025 00:00:00 +0000https://lawzava.com/blog/2025-01-20-reasoning-models-production/Reasoning models are powerful but expensive and slow. Here’s how I integrate them in Go services with routing, async patterns, and cost controls that actually work.https://lawzava.com/blog/2025-01-06-ai-trends-2025/Mon, 06 Jan 2025 00:00:00 +0000https://lawzava.com/blog/2025-01-06-ai-trends-2025/The AI hype cycle is over. 2025 is about the teams who can make this stuff actually work in production – repeatably, measurably, and without burning money.https://lawzava.com/blog/2024-12-23-preparing-for-2025/Mon, 23 Dec 2024 00:00:00 +0000https://lawzava.com/blog/2024-12-23-preparing-for-2025/The AI advantage in 2025 goes to teams that ship measurable workflows, not teams that chase capabilities. The gap is discipline, not technology.https://lawzava.com/blog/2024-12-16-year-in-review-2024/Mon, 16 Dec 2024 00:00:00 +0000https://lawzava.com/blog/2024-12-16-year-in-review-2024/2024 was the year AI stopped being exciting and started being useful. The demo phase ended. The production phase began. Discipline won.https://lawzava.com/blog/2024-12-09-ai-infrastructure-scale/Mon, 09 Dec 2024 00:00:00 +0000https://lawzava.com/blog/2024-12-09-ai-infrastructure-scale/AI infrastructure at scale is just infrastructure. The same boring patterns – gateways, caching, circuit breakers, budgets – solve the same boring problems.https://lawzava.com/blog/2024-12-02-building-ai-teams/Mon, 02 Dec 2024 00:00:00 +0000https://lawzava.com/blog/2024-12-02-building-ai-teams/Most AI team failures come from unclear ownership and weak evaluation, not missing talent. Structure and discipline beat hiring sprees.https://lawzava.com/blog/2024-11-25-ai-model-comparison-2024/Mon, 25 Nov 2024 00:00:00 +0000https://lawzava.com/blog/2024-11-25-ai-model-comparison-2024/There’s no best model. There’s the model that fits your workload, latency budget, cost constraint, and ops tolerance. Here’s how to compare them.https://lawzava.com/blog/2024-11-11-ai-safety-production/Mon, 11 Nov 2024 00:00:00 +0000https://lawzava.com/blog/2024-11-11-ai-safety-production/AI safety in production isn’t a research problem. It’s defense in depth, the same way cyber defense works – layered controls, assumed breach, observable boundaries.https://lawzava.com/blog/2024-10-28-advanced-agent-patterns/Mon, 28 Oct 2024 00:00:00 +0000https://lawzava.com/blog/2024-10-28-advanced-agent-patterns/Single-prompt agents break on real tasks. Plan-execute-replan, orchestrated specialists, structured memory, and explicit recovery are what survive – in Go.https://lawzava.com/blog/2024-10-14-ai-cost-benchmarking/Mon, 14 Oct 2024 00:00:00 +0000https://lawzava.com/blog/2024-10-14-ai-cost-benchmarking/Price-per-token is the least useful number on your AI bill. Real cost benchmarking starts with your workload, not a provider’s pricing page.https://lawzava.com/blog/2024-09-30-retrieval-strategies-rag/Mon, 30 Sep 2024 00:00:00 +0000https://lawzava.com/blog/2024-09-30-retrieval-strategies-rag/Most RAG failures are retrieval failures. Hybrid search, smarter chunking, query expansion, and reranking – measured separately from generation.https://lawzava.com/blog/2024-09-16-technical-documentation-ai/Mon, 16 Sep 2024 00:00:00 +0000https://lawzava.com/blog/2024-09-16-technical-documentation-ai/AI is a decent drafting assistant for technical docs. It’s a terrible replacement for ownership.https://lawzava.com/blog/2024-09-02-ai-code-migration/Mon, 02 Sep 2024 00:00:00 +0000https://lawzava.com/blog/2024-09-02-ai-code-migration/I used LLMs to help migrate a 200K-line Go codebase. The mechanical parts went fast. Everything else was still hard.https://lawzava.com/blog/2024-08-19-llm-testing-strategies/Mon, 19 Aug 2024 00:00:00 +0000https://lawzava.com/blog/2024-08-19-llm-testing-strategies/LLM outputs are non-deterministic. That doesn’t mean you can’t test them rigorously. Here’s the layered testing approach I use in production.https://lawzava.com/blog/2024-08-05-small-models-big-impact/Mon, 05 Aug 2024 00:00:00 +0000https://lawzava.com/blog/2024-08-05-small-models-big-impact/Everyone reaches for GPT-4 by default. Most production tasks don’t need it. Small models are faster, cheaper, and often better when the task is well-defined.https://lawzava.com/blog/2024-07-22-context-window-strategies/Mon, 22 Jul 2024 00:00:00 +0000https://lawzava.com/blog/2024-07-22-context-window-strategies/Bigger context windows aren’t an excuse to stop thinking about what goes into them. Most teams are paying for irrelevant tokens and wondering why quality degrades.https://lawzava.com/blog/2024-07-08-function-calling-patterns/Mon, 08 Jul 2024 00:00:00 +0000https://lawzava.com/blog/2024-07-08-function-calling-patterns/Function calling is how LLMs touch real systems. Treat tools like APIs, arguments like untrusted input, and permissions like the model is an intern with root access.https://lawzava.com/blog/2024-06-24-claude-35-sonnet-analysis/Mon, 24 Jun 2024 00:00:00 +0000https://lawzava.com/blog/2024-06-24-claude-35-sonnet-analysis/Claude 3.5 Sonnet changes model routing math for coding, cost, latency, and production AI workloads.https://lawzava.com/blog/2024-06-10-ai-compliance-enterprise/Mon, 10 Jun 2024 00:00:00 +0000https://lawzava.com/blog/2024-06-10-ai-compliance-enterprise/Compliance doesn’t have to slow you down. But you have to build it into the system from day one, not bolt it on after the demo impresses the board.https://lawzava.com/blog/2024-06-03-enterprise-ai-adoption/Mon, 03 Jun 2024 00:00:00 +0000https://lawzava.com/blog/2024-06-03-enterprise-ai-adoption/Most enterprise AI projects die between the demo and production. The blockers aren’t technical – they’re organizational. Here’s what I keep seeing.https://lawzava.com/blog/2024-05-27-building-voice-ai/Mon, 27 May 2024 00:00:00 +0000https://lawzava.com/blog/2024-05-27-building-voice-ai/Voice AI is ready to ship. The hard parts are latency, interruptions, and knowing when voice is the wrong interface. Here’s how I approach it.https://lawzava.com/blog/2024-05-13-gpt4o-realtime-ai/Mon, 13 May 2024 00:00:00 +0000https://lawzava.com/blog/2024-05-13-gpt4o-realtime-ai/OpenAI shipped a model that sees, hears, and talks back in real time. The demos look magical. The architecture implications are where it gets interesting.https://lawzava.com/blog/2024-04-29-structured-output-patterns/Mon, 29 Apr 2024 00:00:00 +0000https://lawzava.com/blog/2024-04-29-structured-output-patterns/How to get reliable JSON from LLMs in Go with schemas, validation, repair loops, and typed contracts.https://lawzava.com/blog/2024-04-15-ai-developer-tooling/Mon, 15 Apr 2024 00:00:00 +0000https://lawzava.com/blog/2024-04-15-ai-developer-tooling/The AI tooling landscape is exploding. Most of it adds complexity without removing real friction. Here is how I decide what earns a spot in the stack.https://lawzava.com/blog/2024-04-01-agentic-workflows-production/Mon, 01 Apr 2024 00:00:00 +0000https://lawzava.com/blog/2024-04-01-agentic-workflows-production/AI agents that can take actions are fundamentally different from chatbots. The engineering bar must match the blast radius.https://lawzava.com/blog/2024-03-25-prompt-caching-strategies/Mon, 25 Mar 2024 00:00:00 +0000https://lawzava.com/blog/2024-03-25-prompt-caching-strategies/Caching LLM responses is the highest-leverage optimization most teams skip. How I implement it in Go – keys, invalidation, and safety patterns.https://lawzava.com/blog/2024-03-18-multi-model-strategies/Mon, 18 Mar 2024 00:00:00 +0000https://lawzava.com/blog/2024-03-18-multi-model-strategies/Betting on a single model provider is like having a single database with no failover. Here is why multi-model is the only sane production strategy.https://lawzava.com/blog/2024-03-04-claude-3-first-look/Mon, 04 Mar 2024 00:00:00 +0000https://lawzava.com/blog/2024-03-04-claude-3-first-look/Anthropic shipped three models instead of one. That is actually the most interesting part of the release.https://lawzava.com/blog/2024-02-19-evaluating-llm-applications/Mon, 19 Feb 2024 00:00:00 +0000https://lawzava.com/blog/2024-02-19-evaluating-llm-applications/Your LLM feature looks great in demos and breaks in production. Here is how to build an evaluation loop that catches regressions before your users do.https://lawzava.com/blog/2024-02-05-ai-native-architecture/Mon, 05 Feb 2024 00:00:00 +0000https://lawzava.com/blog/2024-02-05-ai-native-architecture/AI-native apps are fundamentally different from a model bolted onto a CRUD app. How I structure them – with code, layers, and hard-won opinions.https://lawzava.com/blog/2024-01-22-local-llms-development/Mon, 22 Jan 2024 00:00:00 +0000https://lawzava.com/blog/2024-01-22-local-llms-development/Local LLMs are finally good enough for development. Use them for iteration, keep the API bills for production.https://lawzava.com/blog/2024-01-08-ai-engineering-discipline/Mon, 08 Jan 2024 00:00:00 +0000https://lawzava.com/blog/2024-01-08-ai-engineering-discipline/AI engineering is not ML research with a product hat. It is the discipline of making models behave in production – and it demands its own skill set.https://lawzava.com/blog/2023-12-25-year-in-review-2023/Mon, 25 Dec 2023 00:00:00 +0000https://lawzava.com/blog/2023-12-25-year-in-review-2023/A personal look back at 2023 – watching AI reshape the industry in real time, and figuring out what matters next.https://lawzava.com/blog/2023-12-18-ai-infrastructure-scale/Mon, 18 Dec 2023 00:00:00 +0000https://lawzava.com/blog/2023-12-18-ai-infrastructure-scale/GPU shortage is real, rate limits are a production constraint, and your AI demo will collapse under real traffic. Annoyed thoughts on infrastructure realism.https://lawzava.com/blog/2023-12-11-multimodal-ai-applications/Mon, 11 Dec 2023 00:00:00 +0000https://lawzava.com/blog/2023-12-11-multimodal-ai-applications/GPT-4V is out and everyone is building vision features. After testing it across real workflows, here is what ships well and what falls apart.https://lawzava.com/blog/2023-12-04-building-with-assistants-api/Mon, 04 Dec 2023 00:00:00 +0000https://lawzava.com/blog/2023-12-04-building-with-assistants-api/I built three things with the Assistants API. One shipped, one got scrapped, and one taught me where the API’s limits really are.https://lawzava.com/blog/2023-11-27-openai-devday-review/Mon, 27 Nov 2023 00:00:00 +0000https://lawzava.com/blog/2023-11-27-openai-devday-review/OpenAI DevDay was not just a product launch. It was a platform play that changes the build-vs-buy calculus for every team shipping AI features.https://lawzava.com/blog/2023-11-13-ai-developer-productivity/Mon, 13 Nov 2023 00:00:00 +0000https://lawzava.com/blog/2023-11-13-ai-developer-productivity/After three months of tracking Copilot and GPT-4 usage across real projects, the productivity picture is messier than the marketing suggests.https://lawzava.com/blog/2023-10-30-llm-security-considerations/Mon, 30 Oct 2023 00:00:00 +0000https://lawzava.com/blog/2023-10-30-llm-security-considerations/LLMs bring security failure modes most teams aren’t defending against. Prompt injection, data leakage, tool abuse, and cost attacks are exploitable today.https://lawzava.com/blog/2023-10-16-responsible-ai-development/Mon, 16 Oct 2023 00:00:00 +0000https://lawzava.com/blog/2023-10-16-responsible-ai-development/Responsible AI is not an ethics committee. It is operational risk management, and teams that treat it otherwise are building liabilities.https://lawzava.com/blog/2023-10-02-ai-technical-debt/Mon, 02 Oct 2023 00:00:00 +0000https://lawzava.com/blog/2023-10-02-ai-technical-debt/AI features create a new species of technical debt that hides in prompts, data pipelines, and model versions. By the time you notice it, the cleanup bill is brutal.