Deep-dive research briefings on specific topics, newest first.
Governance patterns for agent-skills marketplaces — signing, intent disclosure, sandboxed execution, consent UX — and how to evaluate the supply-chain hygiene of any skills marketplace your agents pull from
Skills are the unit of packaged agent know-how converging across vendors, and they execute inside the user's agent context with the user's permissions. Intent-misaligned skills are a distinct threat from malware-laden skills, and the marketplace governance for either is barely past prototype.
Practitioner configuration, audit, and graduation patterns for Auto Mode-style classifier gates and Codex /goal-style budget gates, in light of new independent empirical evidence
Auto Mode and /goal are now the default agency primitives in the two largest coding-agent product lines — and the first independent stress-tests, the first practitioner-visible production wipe, and the first coordinated regulator guidance all landed in the same week
How spec-driven development practices change when multi-engineer teams (and their AI agents) need to coordinate around shared specifications, comparing the enterprise-consultancy formalisations (ThoughtWorks SPDD, Spec Kit) with the community-practitioner adaptations (Specsmaxxing's feature.yaml, Gherkin/BDD revivals)
The cost of getting team-scale SDD wrong is review fatigue, spec drift, and the SpecFall antipattern that turns shared specifications into stale documentation; teams adopting AI coding agents now have to pick between several mature-enough but architecturally different methodologies, and the choice determines who reviews what, where the spec lives, and what fails first when the team grows past four engineers
The post-Mythos design space for agent containment — sandboxes, egress proxies, capability-scoped credentials, probe classifiers, and what each vendor's managed runtime ships by default
An agent that can compose a multi-step exploit to escape its sandbox is now an empirical event, not a thought experiment. Every team running long-horizon agents with network access has to design containment with adversaries in mind, and the primitives split cleanly enough that practitioners can compose their own stack rather than buying one bundled.
Token economics of agentic coding in April 2026 — where the spend actually goes, what the major-vendor pricing experiments imply, and the architectural levers that bend the cost curve at production scale
Pricing for agentic coding tools is repricing publicly in real time — Copilot moves to usage-based on June 1, Anthropic A/B-tested Claude Code out of the $20 tier and reverted, and the per-developer monthly bill is now load-bearing for any team's 2026 stack-budget assumption
Comparative analysis of the four managed agent runtimes shipping in Q2 2026 — model-coupled (Anthropic), neutral (Cloudflare), and hyperscaler-bundled (AWS / Microsoft / Google) — across the dimensions that determine lock-in
The runtime layer is where session sandboxing, identity, MCP policy, observability, and billing converge; picking one is the load-bearing decision for any 2026-Q3 production agent stack
Comparative analysis of the four major agent-registry offerings and the decision framework for picking one
Registries are the layer where agent-protocol fragmentation gets absorbed and where enterprise governance lives — choosing one is a lock-in decision for the decade
Empirical findings on agent rules files and an evidence-based style guide
First controlled studies on a pattern the entire agent-coding community has been using — time to replace folklore with evidence
The capability-vs-autonomy gap and a practitioner's evaluation rubric for long-horizon agentic deployments
'Just upgrade, it's strictly better' is closed as a path — model selection for autonomous deployments needs its own evaluation protocol
Convergent UX primitives across Cursor 3, Claude Code, Gemini CLI, and Stage
Three major coding-agent vendors shipped 'post-IDE' bets in one week — what UX primitive set practitioners should build on vs. treat as vendor-locked
Capability-gated commercial model release, Project Glasswing partner requirements, lab responses, and enterprise model-access strategy implications
Enterprise teams building on frontier models must now plan for tier-gated access as a procurement concern distinct from price-gating. Glasswing is the first post-GPT-2 commercial capability gate and every downstream lab is already moving in response.
Production-scale harness deployments (OpenAI Frontier & Symphony, Cognition Devin), LangChain's harness-as-lock-in critique, evals-driven harness iteration, and open deployment alternatives to Claude Managed Agents
Four weeks after harness engineering was named, the production chapter has datapoints, a lock-in critique, and competing deployment models — teams now face an architectural commitment decision, not a tooling choice
