TAG
#AI
2026-10 4 posts
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In the Agent Era, the Scope a Specialist Software Supplier Can Choose
Part 4 of 4: lock agent features in one dedicated agent, or expose them as tools and work assets any worker can use? It shapes what a supplier can sell.
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Seeds and Germination: Software That Evolves in the Field
Part 3 of 4: fitting a product to each customer site with people and agents, building runtime adaptation into it, and feeding field experience back.
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Every Organization Needs an Agent Runtime
Part 2 of 4: why even air-gapped organizations will run a general-purpose agent runtime on work PCs, and how to connect it to internal models and tools.
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Separating the Worker from the Tool
Part 1 of 4: work spans products, so general-purpose agents become workers and products their tools. What to expose, and where software keeps its value.
2026-09 1 post
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ego-browser and Aside Fail Differently
Same missions, two browser agents: ego-browser isolates its tabs and returned success on missed clicks; Aside works in your real tabs and threw errors.
2026-05 11 posts
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Requirements as Latent State
A requirement is a latent state and the user's sentence a noisy observation. What follows for EARS, spec-driven development, harnesses, and when to ask.
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Skill and Harness
A skill compresses how to behave; a harness organizes how to tell if that behavior nears the goal. Why the two still contain each other in practice.
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Harness as Environment
A vector DB full of experience does not make an agent adapt. That takes a harness: what may change, how success is judged, how far a failure rolls back.
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Memory as Adaptation
Long-running agents need more than a RAG store: why memory split into working, episodic, semantic, and procedural layers that ground policy adaptation.
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Weights, Prompts, Codes as Parameters
If agent problems are POMDPs, weights, prompts, and code are parameters at three layers of one policy space. Why the layers opened in that order.
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Should Databases Handle AI Too?
Oracle 23ai, EDB AIDB, PostgresML, Timescale pgai, pg_aidb — five systems and the abstraction-boundary discussion
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autocorrect.zsh — 167 lines of zsh that fix failed commands
Gemini Flash structured output and zsh preexec/precmd hooks — failed commands fixed in place, no new terminal app
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NVIDIA NIM API — Free Inference for GLM, Kimi, Nemotron, and Gemma 4
build.nvidia.com serves 100+ open models via a free OpenAI-compatible API, no credit card, up to 40 RPM per model. Setup for Claude Code and Cursor.
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10 OpenAI Models Through Quick Benchmarks — The Model Isn't as Smart as You Pay
19 configurations of 10 OpenAI models, 30 runs each on three reasoning problems. gpt-5-nano on minimal scored 4.4%; o1 scored 47.8%, below gpt-4o at 66.7%.
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GitHub Models Inference API — Free Model Access Tested
Call GPT-4.1, DeepSeek R1, and other models free via GitHub Models with a personal access token and the OpenAI Python SDK. Rate and token limits apply.
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Experimenting with the GPT-5 Responses API Web Search Tool
In the GPT-5 Responses API, web search worked with gpt-5 but returned a 400 error on gpt-5-chat-latest. Plus notes on search_context_size and verbosity.
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