{
  "schema_version": "1.1",
  "id": "weekly-2026-08-24",
  "slug": "2026-08-24",
  "issue_number": "007",
  "title": "feed7 Weekly #007",
  "description": "Six ways to make the next agent run safer, leaner, more observable, and easier to evaluate.",
  "published_at": "2026-08-24T00:00:00.000Z",
  "modified_at": "2026-08-23T18:06:59.508Z",
  "url": "https://feed7.dev/weekly/2026-08-24",
  "formats": {
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    "json": "https://feed7.dev/weekly/2026-08-24.json",
    "markdown": "https://feed7.dev/weekly/2026-08-24.md"
  },
  "selection": {
    "rule": "Six source-backed signals and one distraction to leave out.",
    "mode": "ai",
    "ignore_item_id": "auto-cb030de2dd"
  },
  "items": [
    {
      "schema_version": "1.1",
      "id": "auto-137531afb5",
      "slug": "apache-maka-137531afb5",
      "url": "https://feed7.dev/p/apache-maka-137531afb5",
      "title": "apache/maka",
      "why_included": "Use its append-only run log and shared runtime to trim context without losing evidence, inspect failures, and recover crashes.",
      "summary": "Maka gives local coding-agent runs a durable event log, sandbox boundary, recovery path, and shared runtime across desktop, CLI, and evals. It is early, source-only software with changing interfaces.",
      "practical_implication": "Builders can treat prompts as projections of durable run history: trim old tool output from context without deleting evidence, inspect failures, recover crashes, and compare reproducible experiment cells. Its graph mode also uses isolated Git worktrees for parallel implementation.",
      "agent_context": "Apache Maka records model messages, tool calls, results, permission decisions, and termination events in an **append-only local log**. Desktop, CLI, TUI, and evaluations execute through one **Runtime Host**, with sandbox approval for file writes and shell commands.\n\nBuilders can treat prompts as projections of durable run history: trim old tool output from context without deleting evidence, inspect failures, recover crashes, and compare reproducible experiment cells. Its graph mode also uses isolated Git worktrees for parallel implementation.\n\nThis is an **Apache Incubator** project with no approved Apache release. The desktop build currently supports **Apple Silicon macOS**; formats and commands may change, Windows is an unsigned preview, and secrets remain plaintext to the local OS account.",
      "source": {
        "name": "GitHub",
        "url": "https://github.com/apache/maka",
        "published_at": "2026-08-23T00:00:00.000Z"
      },
      "source_class": "tool",
      "content_type": "GitHub Repo",
      "layer": "agent",
      "domains": [
        "coding"
      ],
      "topics": [
        "harness-engineering",
        "agent-reliability",
        "sandboxing"
      ],
      "verification": {
        "status": "needs_review",
        "label": "Needs Review",
        "method": "unverified",
        "verified_at": null
      },
      "uncertainty": [
        "Automatically selected from source material; feed7 has not independently tested the claim."
      ],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-23T00:00:00.000Z",
      "modified_at": "2026-08-23T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/apache-maka-137531afb5",
        "json": "https://feed7.dev/p/apache-maka-137531afb5.json",
        "markdown": "https://feed7.dev/p/apache-maka-137531afb5.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-b3f2ae3bdf",
      "slug": "phantom-gains-auditing-self-improvement-against-a-measur-b3f2ae3bdf",
      "url": "https://feed7.dev/p/phantom-gains-auditing-self-improvement-against-a-measur-b3f2ae3bdf",
      "title": "Phantom Gains: Auditing Self-Improvement Against a Measured Null",
      "why_included": "Add frozen-baseline replicates and a measured null before treating one-decode gains or regressions as real.",
      "summary": "Per-problem self-improvement claims can arise from inference and evaluation noise. This audit argues every transition statistic needs a measured null from frozen baseline replicates.",
      "practical_implication": "For agent and model evaluations, do not treat problem-level gains and losses as ground truth from one decode. Measure each statistic’s null with baseline replicates, then use per-problem tests and false-discovery-rate control.",
      "agent_context": "The study ran three rounds of rank-32 LoRA self-training on Qwen3-8B alongside a frozen control using the same pipeline. It found **seven measurement failures** capable of reversing findings when the control was omitted.\n\nFor agent and model evaluations, do not treat problem-level gains and losses as ground truth from one decode. Measure each statistic’s null with baseline replicates, then use per-problem tests and false-discovery-rate control.\n\nA single greedy decode gave an untrained model an apparent expansion rate of **0.280**, while the replacement exact test detected **nothing on held-out replicates**. Results for problems the base model never solved remained inconclusive, and the method needs more baseline replicates than many studies possess.",
      "source": {
        "name": "arXiv",
        "url": "https://arxiv.org/abs/2608.20290v1",
        "published_at": "2026-08-20T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Paper",
      "layer": "benchmark",
      "domains": [
        "research"
      ],
      "topics": [
        "benchmark-integrity",
        "agent-evals",
        "agent-reliability"
      ],
      "verification": {
        "status": "needs_review",
        "label": "Needs Review",
        "method": "unverified",
        "verified_at": null
      },
      "uncertainty": [
        "Automatically selected from source material; feed7 has not independently tested the claim."
      ],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-20T00:00:00.000Z",
      "modified_at": "2026-08-20T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/phantom-gains-auditing-self-improvement-against-a-measur-b3f2ae3bdf",
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        "markdown": "https://feed7.dev/p/phantom-gains-auditing-self-improvement-against-a-measur-b3f2ae3bdf.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-990ea76696",
      "slug": "break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696",
      "url": "https://feed7.dev/p/break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696",
      "title": "Break It Down, Pass It On: Cross-Task Skill Transfer in LLM Agents",
      "why_included": "Store small textual procedures, because subtask-level skills transferred better while whole-task skills often hurt performance.",
      "summary": "Reusable agent skills transferred better when induced from subtasks and stored as text. Whole-task skills often hurt versus no memory, so retrieval alone is not evidence that a memory helps.",
      "practical_implication": "Build agent memory from small, reusable procedures and prefer textual guidance unless execution requires code. Before retrieval, score candidates for both task specificity and breadth of relevance rather than assuming any prior solution will help.",
      "agent_context": "The study compares task-level against subtask-level skill induction and text against code formats. **Task-level skills often fell below the no-memory baseline**, while **subtask-level skills improved performance on average**; text transferred better than code.\n\nBuild agent memory from small, reusable procedures and prefer textual guidance unless execution requires code. Before retrieval, score candidates for both task specificity and breadth of relevance rather than assuming any prior solution will help.\n\nNeither specificity nor abstractness predicted outcomes alone. Their combined **skill utility score** correlated with transfer performance and requires only skills plus task descriptions, but the supplied material gives no tasks, models, or effect sizes for judging generality.",
      "source": {
        "name": "arXiv",
        "url": "https://arxiv.org/abs/2608.20274v1",
        "published_at": "2026-08-20T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Paper",
      "layer": "agent",
      "domains": [],
      "topics": [
        "skills",
        "agent-memory",
        "agent-reliability"
      ],
      "verification": {
        "status": "needs_review",
        "label": "Needs Review",
        "method": "unverified",
        "verified_at": null
      },
      "uncertainty": [
        "Automatically selected from source material; feed7 has not independently tested the claim."
      ],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-20T00:00:00.000Z",
      "modified_at": "2026-08-20T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696",
        "json": "https://feed7.dev/p/break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696.json",
        "markdown": "https://feed7.dev/p/break-it-down-pass-it-on-cross-task-skill-transfer-in-ll-990ea76696.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-b53948be9f",
      "slug": "give-the-agent-a-budget-not-a-token-sachin-malhotra-anth-b53948be9f",
      "url": "https://feed7.dev/p/give-the-agent-a-budget-not-a-token-sachin-malhotra-anth-b53948be9f",
      "title": "Give the Agent a Budget, Not a Token — Sachin Malhotra, Anthropic",
      "why_included": "Bound write volume, rate, reversibility, and visibility, with human-only overrides outside the agent session.",
      "summary": "Production agents need bounded write authority, infrastructure-stamped identity, and human-only overrides; a broad token and tool list cannot control blast radius.",
      "practical_implication": "Classify write verbs by how failures surface, rate-limit every write, and keep overrides outside agent sessions. Record aggregate behavior with trip wires, size limits using an undo test, and let a trusted proxy stamp agent and session identity.",
      "agent_context": "A cleanup agent’s empty pipeline stage removed its filter, matching and deleting about **200 workloads** used by **20 engineers** in **90 seconds**. The proposed alternative treats authority as budgets across action volume, rate, reversibility, and visibility.\n\nClassify write verbs by how failures surface, rate-limit every write, and keep overrides outside agent sessions. Record aggregate behavior with trip wires, size limits using an undo test, and let a trusted proxy stamp agent and session identity.\n\nThese are production safety primitives, not a guarantee against bad actions. Limits still need tuning by resource and namespace, while quiet or irreversible operations may require a separate human-held credential.",
      "source": {
        "name": "AI Engineer",
        "url": "https://www.youtube.com/watch?v=rbjWzZK2LU0",
        "published_at": "2026-08-22T00:00:00.000Z"
      },
      "source_class": "video",
      "content_type": "Video",
      "layer": "agent",
      "domains": [
        "coding",
        "security"
      ],
      "topics": [
        "harness-engineering",
        "tool-use",
        "sandboxing"
      ],
      "verification": {
        "status": "source_linked",
        "label": "Source Linked",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-22T00:00:00.000Z",
      "modified_at": "2026-08-22T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/give-the-agent-a-budget-not-a-token-sachin-malhotra-anth-b53948be9f",
        "json": "https://feed7.dev/p/give-the-agent-a-budget-not-a-token-sachin-malhotra-anth-b53948be9f.json",
        "markdown": "https://feed7.dev/p/give-the-agent-a-budget-not-a-token-sachin-malhotra-anth-b53948be9f.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-3c0b2ed056",
      "slug": "building-agents-is-trivial-now-context-is-the-next-front-3c0b2ed056",
      "url": "https://feed7.dev/p/building-agents-is-trivial-now-context-is-the-next-front-3c0b2ed056",
      "title": "Building Agents Is Trivial Now, Context Is the Next Frontier — Jeff Ng, Unblocked",
      "why_included": "Retrieve code alongside decisions, incidents, tickets, and conversations so the agent does not repeat a known outage trigger.",
      "summary": "A coding agent with repository access still recommended a known outage trigger. Background agents need reconciled decisions and incident context, not just more raw MCP results.",
      "practical_implication": "For unattended coding agents, retrieve decisions, incidents, tickets, conversations, and code together. Reconcile conflicts, rank relevance, enforce permissions, and provide a synthesized task view rather than making each agent resolve raw MCP output.",
      "agent_context": "An agent investigating QA latency of **3–4 seconds** versus an expected **hundreds of milliseconds** recommended re-enabling async dispatch. It missed a later Slack discussion and Linear postmortem showing that setting had caused an outage.\n\nFor unattended coding agents, retrieve decisions, incidents, tickets, conversations, and code together. Reconcile conflicts, rank relevance, enforce permissions, and provide a synthesized task view rather than making each agent resolve raw MCP output.\n\nThe example demonstrates one corrected recommendation, not a measured reliability gain. Building and maintaining an organization-wide context model also introduces access-control, freshness, and conflict-resolution work.",
      "source": {
        "name": "AI Engineer",
        "url": "https://www.youtube.com/watch?v=HvMyYLTfvhg",
        "published_at": "2026-08-21T00:00:00.000Z"
      },
      "source_class": "video",
      "content_type": "Video",
      "layer": "context",
      "domains": [
        "coding"
      ],
      "topics": [
        "context-engineering",
        "retrieval",
        "mcp"
      ],
      "verification": {
        "status": "source_linked",
        "label": "Source Linked",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-21T00:00:00.000Z",
      "modified_at": "2026-08-21T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/building-agents-is-trivial-now-context-is-the-next-front-3c0b2ed056",
        "json": "https://feed7.dev/p/building-agents-is-trivial-now-context-is-the-next-front-3c0b2ed056.json",
        "markdown": "https://feed7.dev/p/building-agents-is-trivial-now-context-is-the-next-front-3c0b2ed056.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-084c45658e",
      "slug": "vercel-cli-expands-support-for-dns-domains-and-project-c-084c45658e",
      "url": "https://feed7.dev/p/vercel-cli-expands-support-for-dns-domains-and-project-c-084c45658e",
      "title": "Vercel CLI expands support for DNS, domains, and project commands",
      "why_included": "Use structured JSON for DNS, domains, projects, observability, and members while retaining confirmation gates for risky actions.",
      "summary": "Vercel agents can now manage DNS, domains, project state, observability, and members through structured CLI commands, while purchases and destructive actions retain confirmation gates.",
      "practical_implication": "Agent workflows can consume structured JSON output, reducing dashboard handoffs and brittle terminal parsing. Update the CLI before adding these operations to deployment or maintenance scripts.",
      "agent_context": "The Vercel CLI adds dedicated commands for **DNS records**, **domain renewal**, project pause and resume, observability settings, and project membership. DNS updates cover common fields plus SRV-specific settings.\n\nAgent workflows can consume **structured JSON output**, reducing dashboard handoffs and brittle terminal parsing. Update the CLI before adding these operations to deployment or maintenance scripts.\n\nBillable and destructive operations still require **explicit confirmation**. That safeguard limits unattended automation, and domain renewal applies only to domains purchased through Vercel.",
      "source": {
        "name": "Vercel",
        "url": "https://vercel.com/changelog/vercel-cli-expands-support-for-dns-domains-and-project-commands",
        "published_at": "2026-08-21T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Engineering Post",
      "layer": "infra",
      "domains": [
        "coding"
      ],
      "topics": [
        "dev-ux",
        "tool-use",
        "observability"
      ],
      "verification": {
        "status": "official_source",
        "label": "Official Source",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-21T00:00:00.000Z",
      "modified_at": "2026-08-21T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/vercel-cli-expands-support-for-dns-domains-and-project-c-084c45658e",
        "json": "https://feed7.dev/p/vercel-cli-expands-support-for-dns-domains-and-project-c-084c45658e.json",
        "markdown": "https://feed7.dev/p/vercel-cli-expands-support-for-dns-domains-and-project-c-084c45658e.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-cb030de2dd",
      "slug": "stampli-cuts-launch-hours-by-68-using-chatgpt-work-cb030de2dd",
      "url": "https://feed7.dev/p/stampli-cuts-launch-hours-by-68-using-chatgpt-work-cb030de2dd",
      "title": "Stampli cuts launch hours by 68% using ChatGPT Work",
      "why_included": "The 68% time claim lacks workflow, quality, review-burden, and task-level detail, so it offers little reusable guidance.",
      "summary": "Stampli used Codex and ChatGPT Work to cut launch-production hours by 68%, showing how agents can absorb execution work when deadlines and design capacity collide.",
      "practical_implication": "For agent-assisted launches, define the deadline and production scope clearly, then direct agents toward the work that constrained teammates cannot cover.",
      "agent_context": "Stampli used **Codex and ChatGPT Work** to produce launch materials under a fixed deadline, cutting launch-production hours by **68%** and compressing **weeks into days**.\n\nFor agent-assisted launches, define the deadline and production scope clearly, then direct agents toward the work that constrained teammates cannot cover.\n\nThe material does not describe the workflow, output quality, review burden, or which tasks produced the measured reduction.",
      "source": {
        "name": "OpenAI",
        "url": "https://openai.com/index/stampli",
        "published_at": "2026-08-20T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Official Release",
      "layer": "industry",
      "domains": [
        "coding"
      ],
      "topics": [
        "coding-agents",
        "adoption"
      ],
      "verification": {
        "status": "official_source",
        "label": "Official Source",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-08-20T00:00:00.000Z",
      "modified_at": "2026-08-20T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
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        "markdown": "https://feed7.dev/p/stampli-cuts-launch-hours-by-68-using-chatgpt-work-cb030de2dd.md"
      }
    }
  ],
  "agent_instruction": "Use these items as source-backed context. Do not invent claims beyond linked material. Prefer practical implications for solo developer work. If sources conflict, call it out."
}