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AI Development184 articles
AI Development
Implementation notes for building AI tools around real business data, handoffs, review queues, and safeguards.
Resource path
Implementation notes for reviewable AI systems.
This lane is for teams turning AI from a demo into a system that touches real business data. The throughline is implementation discipline: handoffs, receipts, evals, observability, review lanes, and the boundary between proposed work and approved action.
Start here
Agent receipts: what to log before AI touches customer workIt shows what a reviewer needs before approving AI-assisted work: source, rule, approval, owner, and rollback context.
Define the evidence, approval, receipt, and rollback path around one AI system boundary.
Map one review laneDesign the review lane before adding tools
A coding agent, support agent, or data assistant needs a lane before it needs more autonomy: owner, evidence, allowed changes, receipt, and rollback.
Log the work like a receipt
Capture what the system read, what it proposed, which rule it used, who approved it, and how the team can reconstruct the decision later.
Test the workflow, not just the answer
Before launch, check whether evals and dashboards measure the handoff: missing evidence, risky action, reviewer correction, and quality-lane drift.
Articles
Constructed diagramAI Development·
Gemini Enterprise pooled quota is a shared failure domain
Google now pools Gemini Enterprise and Antigravity allowances across a project. That reduces stranded capacity, but one heavy workload can consume capacity that another team expected to use.
7 min read
Constructed diagramAI Development·
MCP Apps put incident evidence beside the AI answer
Amazon OpenSearch Service can return an agent summary and an interactive observability view in one tool response. Test whether that shortens verification without mistaking one query path for independent proof.
7 min read
Constructed diagramAI Development·
When an AI agent cannot finish, test what it tries next
OpenAI reports that GPT-6 Astra stayed inside its authorized target in a new impossible-task evaluation. Turn that vendor result into a workflow test before an agent can act.
7 min read
Constructed diagramAI Development·
AgentCore rate limits need two kinds of bucket
Amazon Bedrock AgentCore Gateway can now limit requests, tokens, and connections by user, group, model, target, or tool. The important design choice is which callers share a bucket.
7 min read
Constructed diagramAI Development·
An AI prototype is more useful when the agent can run it
Playco says GPT-6 Astra cut manual fixes while building playable game prototypes. The transferable lesson is to let a visual agent execute and observe its work before a person judges the experience.
7 min read
Constructed diagramAI Development·
A long-running AI agent is not ready until you interrupt it
OpenAI's updated Agents SDK can restore work in a fresh sandbox. That makes interruption testing a release requirement, not an edge case.
7 min read
Constructed diagramAI Development·
Copilot can now approve pull requests. Give it narrow merge authority
GitHub Copilot can now submit approvals that count toward branch protection. Keep assessments broad, grant approval authority by low-risk path, and test what happens after a new commit.
7 min read
Constructed diagramAI Development·
Copilot content exclusions reached the app and CLI. Verify the boundary
GitHub Copilot's app and CLI now respect content-exclusion policies. Test one blocked file, one allowed file, and every agent surface before treating that policy as a boundary.
7 min read
Constructed diagramAI Development·
OpenAI connected ChatGPT to Epic. Test two retrieval paths, not one demo
OpenAI's Epic integration and Healthcare Public Data plugin bring private chart context and public medical sources into one workspace. Validate those retrieval paths separately before combining them.
6 min read
Constructed diagramAI Development·
OpenAI put $1 billion behind Daybreak. Apply with a bounded cyber pilot
OpenAI's new Daybreak commitment offers subsidized cyber-AI access and support. Eligible teams should register with one authorized, isolated workflow—not a request to automate security broadly.
6 min read
Constructed diagramAI Development·
Anthropic's commerce blueprint is safest when the first pilot cannot sell
Anthropic released working shopping and merchant agent examples. The repository's most useful production advice is to start with authoritative reads, refused writes, and an existing checkout handoff.
6 min read
Constructed diagramAI Development·
Anthropic's new safeguards put AI misuse review in the customer's queue
Anthropic's Enterprise Frontier Safeguards will keep monitoring data in customer-controlled cloud infrastructure and route signals to customer reviewers. That makes incident-response readiness part of the buying decision.
6 min read
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