diff --git a/plans/README.md b/plans/README.md
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+++ b/plans/README.md
@@ -22,6 +22,7 @@ broad, lasting value.
 | [competitive-landscape](competitive-landscape.md) | 7, 12 | New — pre-launch |
 | [audience-analysis](audience-analysis.md) | 7 | New — pre-launch |
 | [measure-project-impact](measure-project-impact.md) | 2, 12 | New — pre-launch |
+| [anticipated-criticisms](anticipated-criticisms.md) | 4, 12 | New — pre-launch |
 
 *Previously had plans for "high-leverage contributions" and "teach and
 document" — these were behavioral norms, not executable plans. Their
diff --git a/plans/anticipated-criticisms.md b/plans/anticipated-criticisms.md
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+# Plan: Anticipated criticisms
+
+**Target sub-goals**: 4 (be honest about failure), 12 (honest arithmetic)
+
+## Problem
+
+Before sharing the project publicly, we should anticipate the criticisms
+it will attract and decide which ones require changes before launch vs.
+which ones we simply acknowledge. Unaddressed valid criticisms will kill
+credibility on first contact.
+
+## Criticism 1: "This was written by an AI"
+
+**Severity: high. This could undermine the entire project.**
+
+The git history shows every commit authored by `claude`. The CLAUDE.md
+file is literally instructions for an AI assistant. An AI-authored
+framework about the costs of AI will strike many people as:
+
+- **Ironic/hypocritical** — the project consumed significant compute
+  to produce a document about compute costs.
+- **Untrustworthy** — LLMs confabulate. Why should anyone trust an LLM's
+  estimates about LLM costs?
+- **Self-serving** — is this Anthropic's product trying to appear
+  responsible?
+
+**What to do:**
+
+- Be transparent about it upfront. The landing page or README should
+  state clearly that this was developed in collaboration with Claude,
+  and that this is part of the point — can an AI conversation produce
+  value that exceeds its own cost?
+- Disclose the project's own estimated cost (conversations, compute,
+  energy) alongside the methodology. Eat our own cooking.
+- Emphasize the human editorial role — you directed, reviewed, and
+  are publishing this. The AI was a tool, not the author.
+- Frame the irony as a feature: "We used the methodology to evaluate
+  the methodology."
+
+**Status**: Must address before launch.
+
+## Criticism 2: "Your numbers are wrong"
+
+**Severity: medium. Expected and manageable.**
+
+The methodology openly states most estimates have low confidence.
+But specific numbers will be challenged:
+
+- Our energy estimates (100-250 Wh per long conversation) may be too
+  high compared to Google's published data (0.24 Wh per median prompt).
+  A "long conversation" has many turns, but the gap is still large.
+- Our compute cost estimate (~$50-60 per conversation) will be disputed
+  by anyone who knows inference pricing.
+- Training amortization methods are debatable.
+
+**What to do:**
+
+- Calibrate environmental estimates against Google (Aug 2025) and
+  "How Hungry is AI" (May 2025) published data before launch.
+- Show the math explicitly. Let people check it.
+- Make it easy to substitute different parameters.
+- The "Related work" section (from competitive-landscape plan) will
+  help here — it shows we know the literature.
+
+**Status**: Should address before launch (calibration task).
+
+## Criticism 3: "The social costs are just hand-waving"
+
+**Severity: medium. Valid but defensible.**
+
+Categories like "cognitive deskilling," "epistemic pollution," and
+"power concentration" are named but not quantified. Quantitative
+researchers will dismiss these as soft.
+
+**What to do:**
+
+- Cite the empirical research that exists: CHI 2025 deskilling study,
+  endoscopy AI dependency data, Microsoft Research survey. This moves
+  the categories from speculation to evidence-informed.
+- Be explicit that naming unquantifiable costs is a deliberate design
+  choice. The alternative — ignoring them — is worse. "The quantifiable
+  costs are almost certainly the least important ones" is already in
+  the README. Keep it.
+- Do not pretend to quantify what cannot be quantified.
+
+**Status**: Partially addressed. Add citations to the methodology.
+
+## Criticism 4: "This discourages AI use"
+
+**Severity: low-medium. Depends on audience.**
+
+Some will read this as anti-AI activism disguised as accounting. Tech
+optimists will push back on the framing.
+
+**What to do:**
+
+- The methodology already includes positive impact metrics (reach,
+  counterfactual, durability). Emphasize these. The goal is not zero
+  usage but net-positive usage.
+- The landing page should make clear this is a decision-making tool,
+  not a guilt tool. "When is AI worth its cost?" not "AI is too costly."
+- Avoid activist language. Let the numbers speak.
+
+**Status**: Mostly addressed. Landing page framing could be refined.
+
+## Criticism 5: "The toolkit only works with Claude Code"
+
+**Severity: medium for adoption, low for methodology.**
+
+The impact-toolkit is Claude Code-specific (hooks, context compaction
+events). This limits the toolkit's reach to one product.
+
+**What to do:**
+
+- Acknowledge this honestly. The toolkit was built for the environment
+  we had access to.
+- The methodology is tool-agnostic. Separate the methodology's value
+  from the toolkit's portability.
+- If there is demand, the hook architecture could be adapted for other
+  tools. But don't over-promise.
+
+**Status**: Acceptable for launch. Note the limitation.
+
+## Criticism 6: "No peer review, no institutional backing"
+
+**Severity: medium. Especially for segments B (researchers) and C (ESG).**
+
+This is one person's side project with AI assistance. No university,
+no journal, no standards body behind it.
+
+**What to do:**
+
+- Don't pretend otherwise. CC0 licensing and an open issue tracker are
+  the peer review mechanism. Invite scrutiny.
+- A DOI (via Zenodo or similar) would add citability without requiring
+  formal peer review. Low effort, meaningful for academic audiences.
+- Adoption by even one external researcher would provide social proof.
+
+**Status**: Consider Zenodo DOI before launch. Not blocking.
+
+## Criticism 7: "The cost estimates for this project itself don't add up"
+
+**Severity: high if we claim net-positive without evidence.**
+
+We estimated $2,500-10,000 in compute costs for the conversations that
+produced this project. If we claim the project is net-positive, that
+claim will be scrutinized.
+
+**What to do:**
+
+- Do not claim net-positive at launch. We cannot know yet.
+- State the costs honestly. State what threshold of engagement would
+  justify them (see measure-project-impact plan).
+- Let the outcome speak for itself over time.
+
+**Status**: Addressed by measure-project-impact plan. Don't overclaim.
+
+## Criticism 8: "You're reinventing the wheel"
+
+**Severity: low if we handle positioning well.**
+
+People who know CodeCarbon or EcoLogits will ask why we didn't just
+contribute to existing projects.
+
+**What to do:**
+
+- The "Related work" section must make clear we know these tools exist
+  and see ourselves as complementary, not competing.
+- Our scope is different: taxonomy + framework vs. measurement tool.
+- Link to existing tools prominently.
+
+**Status**: Addressed by competitive-landscape plan.
+
+## Priority order for pre-launch
+
+1. **Address criticism 1** — Add transparency about AI authorship to
+   the landing page and README. Disclose project costs.
+2. **Address criticism 2** — Calibrate estimates against published data.
+3. **Address criticism 3** — Add citations for social cost categories.
+4. **Address criticism 6** — Consider Zenodo DOI.
+5. Remaining criticisms are manageable with existing content or minor
+   framing adjustments.
+
+## Honest assessment
+
+Criticism 1 (AI authorship) is the most dangerous. If the first reaction
+is "an AI wrote this about AI costs, how convenient," the methodology
+won't get a fair reading. Transparency and self-measurement are the only
+defenses. The project must demonstrate that it holds itself to the same
+standard it proposes for others.