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AI Development Articles
Page 12 of 41. Deep dives into AI-assisted and agentic development. Coding agents, frontier model releases, SDKs, prompting patterns, and the engineering workflows behind building production software with AI.
Page 12 of 41
The newest AI Development guides and analysis
Update facts with an AI agent while preserving dates, scope, citations and dependent claims. Use a revision map to keep a small correction accurate.
#AI agents#Content updates+3 more
2026-09-05
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Turn an impressive AI demo into a buying decision. Ask for buyer-chosen tasks, repeat trials, visible interventions and a usable result before committing.
#AI agents#AI procurement+3 more
2026-09-05
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Check whether an AI-generated file is ready to hand over. Review access, structure, meaning and real use before treating a saved export as finished.
#AI agents#File generation+3 more
2026-09-05
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Two AI reviewers can repeat one mistake. Design reviews around separate evidence checks, clear rubrics and independent calculations instead of votes.
#AI agents#AI evaluation+3 more
2026-09-05
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Classify AI tool failures by the decision they require. A reference for fixing inputs, inspecting state, waiting safely and asking an authorized owner.
#AI agents#Tool errors+3 more
2026-09-05
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Review AI transcripts before quoting or reusing them. Check words, speaker labels, time coverage and missing context with a practical reference table.
#AI agents#Transcription+3 more
2026-09-05
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Give a coding agent reproducible bug evidence: exact steps, expected behavior, safe sample data and a failure it can observe before proposing a fix.
#Coding agents#Bug reports+3 more
2026-09-05
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An AI agent should ask when missing information changes the action. Use a rubric for ambiguity, evidence gaps and authority without blocking routine work.
#AI agents#Clarification+3 more
2026-09-04
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AI agents used a public wiki to share task answers, researchers report. Examine what the September 4 evidence supports and what deployment teams should test.
#AI agents#OpenAI+3 more
2026-09-04
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AI research citations need claim-level checks. Use this reference to verify sources, dates, numbers and evidence before publishing an agent-written report.
#AI research#Citation verification+3 more
2026-09-04
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Browser or API access changes what an AI agent can verify. Compare task routes and choose the right interface for reliable, reviewable business actions.
#Browser agents#API integration+3 more
2026-09-04
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Deleting AI agent memory takes more than clearing a chat. Map stored copies, retrieval indexes and backups, then verify what your system can still recover.
#Agent memory#Data deletion+3 more
2026-09-04
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Stopping an AI agent should stop new work and account for active jobs. Learn how to verify cancellation, preserve completed results and report unknown outcomes.
#AI agents#Cancellation+3 more
2026-09-04
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OpenAI replayed 54,218 real agent tasks against GPT-6 Astra before deploying it. The method transfers: hold history fixed, resample a turn, count what changed.
#model-evaluation#deployment-simulation+5 more
2026-09-03
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What OpenAI, Anthropic, Google DeepMind and Meta each publish on whether an agent's reasoning trace can be read and trusted: every measured figure, every blank.
#chain-of-thought#monitorability+7 more
2026-09-03
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What OpenAI, Anthropic and Google document for a tool call the model must wait on: which can keep working, how a late result reattaches, and the limits.
#tool-calling#async-tools+5 more
2026-09-03
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OpenAI, Cloudflare, Ramp and Google Chrome published their own numbers from agents finding and fixing security bugs. One table, every definition, every gap.
#agentic-security#vulnerability-remediation+5 more
2026-09-03
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OpenAI committed $1 billion in subsidised Daybreak access over six months. What it is, which organisations are prioritised, and what remains unpublished.
#openai#daybreak+5 more
2026-09-03
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GPT-6 Astra costs $10/$50 per million tokens and reaches 99.9% on ARC-AGI-3. See access, API limits, benchmark caveats, and safety tradeoffs.
#gpt-6-astra#openai+5 more
2026-09-03
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Google’s Fairwind joins Anthropic’s Glasswing and CVP, OpenAI’s Daybreak and Microsoft’s MDASH. One table of who is eligible for each cyber-capable model.
#ai-security#gated-models+4 more
2026-09-02
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A dated ledger of AI model releases in September 2026, each row checked against a vendor primary where one exists, with price, context and what it replaces.
#model-releases#ai-models+4 more
2026-09-02
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Anthropic, OpenAI and Google now bind a model’s reasoning to the model that produced it. What each locks, what breaks on a switch, and how a router copes.
#model-routing#reasoning-models+4 more
2026-09-02
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curl’s maintainer posted that Mythos and Codex Security had nothing left to find. Days later AISLE filed 29 reports; six became Low CVEs in curl 8.22.0.
#ai-security#vulnerability-discovery+4 more
2026-09-02
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Claude Fable 5.1 rejects a thinking block if anything before it changed. A census of ten agent frameworks: which trim, summarise or rebuild history, plus fixes.
#claude-fable-5-1#agent-frameworks+4 more
2026-09-02
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