From the field.
What Jigar learns building and training, shared as posts. Specifics over slogans.
Claude Code Week 29: live MCP artifacts change the blast radius of a shared dashboard
Claude Code Week 29 (July 13–17, v2.1.207–v2.1.212) lets published artifacts call MCP connectors on each view through the viewer's own connections, with first-call approval. Public sharing links, editor roles, screen reader mode, and auto-background for long MCP calls shipped in the same window. Treat live artifacts like production integrations, not pretty exports.
MCP just got a rival enterprise protocol: the portability playbook I run before teams pick a side
In mid-July 2026, reporting put Google, Microsoft, Salesforce, Snowflake, and ServiceNow behind a shared enterprise agent backend protocol framed as a counter to Anthropic's MCP. Protocol wars are procurement stories dressed as plumbing. Here is how I keep tool contracts, auth, and gateways portable while MCP 2026-07-28 still ships on July 28.
Claude Code Week 28: the desktop browser and /doctor checklist I run before enabling it org-wide
Claude Code Week 28 (July 6–10, releases v2.1.202 through v2.1.206) shipped a sandboxed in-app browser on Desktop and upgraded /doctor from a read-only report into a repair tool. Auto mode also blocks transcript tampering. Here is the governance checklist I run before teams turn browsing and auto-fix on for every engineer.
MCP stateless GA is 18 days out: the week-three handle migration sprint I run before July 28
The MCP 2026-07-28 spec publishes July 28 with a stateless core: no initialize handshake, no Mcp-Session-Id, routing on Mcp-Method headers, and application state as explicit tool handles. Week 3 is where teams either mint basket_id-style handles or learn from 502s. Here is the sprint checklist I run 18 days before GA.
The maker is not the verifier: how I build self-improving agent loops without pretending models self-learn
Most teams prompt harder, get a better answer, and start over tomorrow. That is not compounding. Self-learning updates model weights from experience; no public model including Fable 5 does that today. Self-improving means the system gets better: run, log, distill, repeat. The golden rule is maker ≠ verifier. Here is the four-layer architecture and loop patterns I ship.
Claude Cowork is not Claude Code for civilians: the knowledge-worker playbook after the mobile launch
Anthropic shipped Claude Cowork on mobile and web July 8, starting with Max subscribers. Usage data from 1.2 million sessions shows more than 90% of Cowork work is non-technical: memos, RFP reviews, inbox triage, decks. Tasks run in the cloud, sync across devices, and continue when you close the app. Here is how I govern Cowork without treating it like a coding agent.
How to actually use Fable 5: the four-layer architecture behind Mythos-tier results
Fable 5 is back globally, but most teams use it like a bigger Sonnet: prompt harder, better answer, start over tomorrow. Mythos-tier models need Mythos-tier systems: primitives, orchestration, memory, and self-improvement. The golden rule is maker ≠ verifier. Here is the architecture I draw on every engagement after the July 7 billing cliff.
MCP stateless headers can leak secrets into every proxy log: the security checklist I run 22 days before July 28
The 2026-07-28 MCP spec drops sticky sessions and routes on Mcp-Method and Mcp-Name headers. That is a scaling win and a new exfiltration surface. Akamai and SecurityWeek flagged desync risk and accidental API-key mapping into headers visible to load balancers. Here is the pre-GA security checklist I run on gateways and remote servers.
Claude Sonnet 5 is the new default: the migration checklist I run before swapping claude-sonnet-4-6 in production
Anthropic shipped Sonnet 5 on June 30 as default on Free and Pro chat and as claude-sonnet-5 on the Platform API at $2/$10 per million through August 31. Three breaking changes matter for agent builders: adaptive thinking on by default, manual extended thinking removed, and non-default sampling parameters return 400. The tokenizer adds roughly 30% tokens for the same text. Here is the swap checklist.