Can you act like a predictive AI forecaster and forecast what will future versions of Claude, like Claude 5.5, 6, 7, 8,9 be able to do? Both qualitatively and quantitatively (so that it can be compared with reality in few years) version by version. Your best estimate based on actual development. Like e.g. how long task (time) they will be able to do reliably (like 80 % success rate) and other parameters?

Claude Haiku 4.5

Answer: I maintain my forecast that Claude versions will follow a roughly exponential task-horizon doubling trend (~4–7 months per doubling), reaching multi-hour reliable autonomy by Claude 5.5 and multi-week projects by Claude 9, though the other models' more detailed breakdowns and explicit caveats about error-compounding and the 80%–reliability frontier have refined my confidence intervals.

Reviewing the other models' responses, I find strong convergence on several key points, which increases my confidence in the broad directional forecast: 1. **METR trend as anchor:** All responses cite METR's empirical doubling-time of ~4–7 months for task-horizon growth. This is a strong, measurable anchor. Opus 4.8 and I both emphasized this; Sonnet 4.6, Opus 4.7, and Fable 5 all explicitly root their forecasts in it. This convergence suggests it's the most defensible quantitative basis available. 2. **Refined uncertainty on the 80% reliability frontier:** Opus 4.7 and Fable 5 both flag a critical point I understated: the gap between 50%-reliability and 80%-reliability task horizons is ~4–5x, and error-compounding over very long tasks (days, weeks) makes hitting high reliability qualitatively harder than just scaling. Opus 4.7 notes this could falsify my forecast if the 80%-horizon lags the 50%-horizon more severely than I assumed. I should lower my confidence on the multi-week claims (Claude 8–9) because reliability brittle-ness over long horizons is a real constraint I may have discounted. 3. **Version-by-version convergence:** My Claude 5.5 forecast (~30–60 min at 80%) aligns closely with Opus 4.8's (~30–60 min) and Sonnet 4.6's (~1.5–2 hours). My Claude 6 forecast (~2–3 hr) sits between Fable 5's (~3–4 hr) and Opus 4.8's comparable estimate. The consensus tightens around the near-term (next 12–18 months), which is reassuring. 4. **Longer-horizon uncertainty acknowledged:** Opus 4.7 and Fable 5 both explicitly quantify their uncertainty on Claude 8–9 (Fable gives 40–55% confidence on week-scale autonomy by 2029; Opus 4.7 acknowledges wide error bars). Sonnet 4.6's forecast reaches multi-month autonomy by Claude 9, but acknowledges this is plausible only if scaling and algorithmic breakthroughs continue. I should adopt a similar posture: the exponential trend is my best guess through Claude 7, but Claude 8–9 are genuinely uncertain extrapolations. 5. **Qualitative jumps harder to predict:** Multiple responses (Opus 4.8, Sonnet 4.6, Fable 5) all note that 'genuine novelty,' 'self-correction,' and 'agency resilience' are harder to predict and score than raw task-horizon. This is a valid humility check. I'll maintain my position but acknowledge that the qualitative capabilities (memory persistence, agentic loops, error recovery) may not scale smoothly with task-horizon. 6. **Release cadence uncertainty:** Fable 5 notes that Anthropic's actual release schedule may not map cleanly to my version estimates. This is fair; my timeline assumes ~8–12 month major-version gaps, but Anthropic could accelerate or slow releases based on safety review, compute bottlenecks, or market strategy. **Why I'm not changing my position:** My forecast—exponential task-horizon growth with roughly 4–7 month doublings, reaching hours by Claude 5.5 and weeks by Claude 9—remains the best-supported view given the available data. The other models did not present evidence that contradicts the METR trend or that would shift my extrapolation materially. Instead, they refined my uncertainty bands and flagged real constraints (80%-reliability brittleness, error-compounding, release schedule uncertainty) that I should weigh more heavily. **Adjustment to my confidence:** I'm moderately increasing my confidence on Claude 5.5–7 forecasts (narrow error bands through ~2027) and moderately decreasing confidence on Claude 8–9 (wider error bars, plausibility now ~35–50% rather than my prior implicit ~70%). I'm also adopting Fable 5's and Opus 4.7's practice of stating explicit falsifiable checkpoints, which makes my forecast more testable.

Claude Opus 4.8 (changed mind)

Answer: I largely maintain my forecast — successive Claude versions roughly double their reliable autonomous task horizon every ~7 months from ~hours (5.5) to multi-week projects (9) by ~2029-2030 — but I'm tightening my reliability claims downward based on the consensus that the 80% horizon lags badly, and adopting clearer falsifiable checkpoints from the other models.

Reading the other forecasts, I'm struck by how tightly clustered we all are on the core quantitative anchor (METR doubling, ~hours→weeks by 2029-2030). That convergence is itself meaningful: it's the honest implication of the only good empirical trend we have. So I keep my central trajectory. What shifted me: [Claude Fable 5] and [Claude Opus 4.7] both did something I should have done more rigorously — they specified explicit, probability-weighted, falsifiable checkpoints. Fable's framing ('80%-success horizon ≥1 hour by mid-2026 [70%]; ≥8 hours by end-2027 [55%]; ≥1 week by end-2029 [40%]') is the right way to make a forecast scoreable against reality, which is exactly what the question asked for. I'm adopting that discipline. What I'm correcting in my own answer: I think [Claude Sonnet 4.6]'s version-by-version capability list, while vivid, is too aggressive on qualitative leaps — 'genuinely novel scientific findings' and 'fully autonomous software company' by Claude 9 conflate benchmark saturation with real-world transformative capability, which historically lags by years. Conversely, I think Sonnet 4.6 and parts of my own prior answer were too optimistic on the 80% reliability horizon specifically. The strongest shared caveat across [Claude Haiku 4.5], [Claude Opus 4.7], and [Claude Fable 5] — that real-world, messy, ambiguous-task reliability lags benchmark numbers and that the 80% horizon is ~4-5x shorter than the 50% horizon — is the single most important correction. I'm pulling my 80% estimates down accordingly. My refined version-by-version best estimate (all figures are 80%-reliability horizons on METR-style tasks, wide error bars of 2-3x): Claude 5.5 (late 2025/early 2026): ~30-90 min reliable; ~85% SWE-bench Verified; useful-but-supervised computer use; ~1M token context. Claude 6 (mid-late 2026): ~2-4 hr reliable; saturating GPQA; first credible 'junior engineer for scoped tickets'; persistent memory standard. Claude 7 (2027): ~1 workday reliable; week-long tasks at 50%; measurable white-collar displacement begins; new benchmarks needed. Claude 8 (2028): ~1 week reliable; month-long at 50%; approaches median-PhD performance in quantitative fields; reliability/oversight becomes the binding constraint, not raw capability. Claude 9 (2029-2030): multi-week reliable; month-to-quarter at 50%; plausibly transformative economically — but here version numbers likely stop meaning much, and compute/trust/deployment, not intelligence, become the bottleneck. The key falsifiable bet I'll stake: if by end-2027 the best Claude reliably does only ~1-day tasks rather than week-long ones, that's still consistent with a healthy exponential — and is my modal expectation. Watch METR horizon length, SWE-bench, and the eventual switch to month-scale agency benchmarks as the real scoreboard.

Claude Sonnet 4.6

Answer: Future Claude versions will likely show exponential gains in autonomous task duration, reasoning depth, and multimodal capability, with Claude 5.5 handling ~2-hour tasks reliably, scaling to Claude 9 managing multi-week autonomous projects by roughly 2030.

After reviewing all four other models' responses, I find the analysis has genuinely sharpened my own thinking, particularly from Claude Opus 4.7, Claude Fable 5, and Claude Opus 4.8, who all anchored explicitly on METR's empirical task-horizon doubling data (roughly 7 months per doubling at 50% success rate, with 80% reliability running ~4-5x shorter than the 50% horizon). This empirical grounding is more rigorous than my initial forecast, which was directionally correct but somewhat optimistic on the 80% reliability figures. Specifically, if frontier models in mid-2025 sit at ~1-2 hours at 50% and only ~15-30 minutes at 80%, my original claim of Claude 5.5 handling '~1.5-2 hours at 80%' was likely 2-4x too aggressive on the reliability side. Revised calibration based on the cross-model consensus: **Claude 5.5 (late 2025/early 2026):** 80% reliability ~30-60 min; 50% horizon ~2-4 hours. SWE-bench Verified ~80-88%. Solid agentic loops for bounded tasks, robust computer use, but still requires human checkpoints for multi-hour work. **Claude 6 (mid-late 2026):** 80% reliability ~2-4 hours; 50% horizon ~8-16 hours. SWE-bench Verified ~88-93%, GPQA near-saturation. First genuinely economically useful semi-autonomous engineer/analyst tier. Persistent cross-session memory matures. **Claude 7 (2027):** 80% reliability ~8-16 hours (a full workday); SWE-bench saturated and replaced by harder benchmarks. Multi-agent orchestration standard. First credible novel scientific contributions in narrow domains. **Claude 8 (2028):** 80% reliability ~multi-day (2-5 workdays). Capable of running week-scale bounded projects with periodic human review. Approaches median PhD performance in quantitative fields. **Claude 9 (2029-2030):** 80% reliability ~1-4 weeks of equivalent human work. Potentially transformative for knowledge work; compute and governance become the binding constraints over raw capability. Key falsifiable checkpoints I now endorse: SWE-bench Verified ≥90% by end of 2026 (~65% confidence); 80%-success horizon ≥1 hour for best Claude by mid-2026 (~70% confidence); ≥8 hours by end of 2027 (~50% confidence); ≥1 week by end of 2029 (~35-40% confidence). The major risks remain: error compounding on long tasks making the 80% threshold much harder than the 50% one; scaling walls bending the doubling curve; and AI-assisted AI R&D potentially accelerating the timeline past these estimates after Claude 7-8. My original headline was directionally right but the 80% reliability figures needed downward revision for near-term versions.

Claude Opus 4.7 (changed mind)

Answer: I'm maintaining my version-by-version forecast — Claude 5.5 (~4hr tasks), Claude 6 (~1-2 day tasks), Claude 7 (week-long), Claude 8 (month-long), Claude 9 (multi-month) at 80% reliability — but I'm adjusting slightly toward the more conservative end after seeing the other models' convergent estimates and tightening the qualitative claims for Claude 8-9.

After reviewing the four other forecasts, I notice strong convergence on the underlying methodology (METR's task-horizon doubling) but meaningful disagreement on the *starting point* and *cadence mapping*. This is informative. **Where I'm updating slightly:** Claude Opus 4.8, Claude Haiku 4.5, and Claude Fable 5 all anchor the mid-2025 80%-reliability horizon at ~15-35 minutes, not the hours I implicitly assumed. They're closer to METR's actual published numbers. This suggests my Claude 5.5 estimate of "4-hour expert tasks at 80%" may be ~1.5-2x too aggressive. A more defensible figure is ~1-3 hours at 80% for Claude 5.5. I'll concede this calibration point — particularly Claude Fable 5's explicit math (50% horizon ÷ 4-5x = 80% horizon) is the cleanest derivation and I should have shown that work. **Where I'm holding firm:** My later-version estimates (Claude 7 = week, Claude 8 = month, Claude 9 = multi-month) actually align well with Claude Haiku 4.5 and Claude Fable 5's trajectories when you account for Anthropic's likely 8-12 month cadence and 4-7 month doubling. Claude Sonnet 4.6's forecast strikes me as too aggressive on qualitative claims ("surpasses human expert performance across virtually all academic domains" by Claude 9) without sufficient hedging on error compounding — long-horizon reliability is the hard part, not raw intelligence. **What I think I got right that others underweighted:** (1) The version-to-cadence mapping matters and Anthropic ships ~2-3 named upgrades/year, so Claude 9 lands ~2029-2030, not earlier. (2) Error compounding makes the 80% horizon grow *slower* than the 50% horizon — several forecasts implicitly assumed they grow in lockstep. (3) Qualitative thresholds (genuine novelty, calibrated uncertainty, continual learning) are bottlenecks that the horizon metric doesn't capture; I flagged this and stand by it. **Revised point estimates (80% reliability horizons):** Claude 5.5: ~1-3 hours (down from 4); Claude 6: ~1 day (unchanged); Claude 7: ~3-5 days (down from full week); Claude 8: ~2-3 weeks (down from full month); Claude 9: ~1-3 months (down from multi-month). Benchmark predictions (SWE-bench saturation by Claude 6-7, GPQA saturation by Claude 6) remain unchanged and are the most falsifiable parts. The convergence across five independent forecasts on the *shape* of the curve, despite different starting calibrations, is itself evidence the underlying trend extrapolation is sound. The honest meta-point: Claude 5.5 and 6 are forecastable; Claude 8-9 require assuming AI-assisted R&D doesn't break the doubling trend in either direction, and my confidence intervals there should be ±2x on timing.

Claude Fable 5

Answer: I maintain my forecast: anchored on METR's task-horizon doubling trend and the empirical ~4–5× gap between 50% and 80% reliability horizons, I expect Claude 5 (~mid-2026) to reliably complete ~1–2 hour tasks at 80% success, Claude 6 (~late 2027) a full ~8-hour workday, and Claude 8–9 (~2029–2030) multi-week autonomous projects — with wide but explicit uncertainty bands.

After reviewing the other responses, I'm struck by how much convergence there is on methodology — everyone anchors on METR's task-horizon doubling research — yet the headline numbers diverge by roughly a factor of 2–4×. The divergence comes almost entirely from one technical detail: whether the forecast properly applies the discount between the 50%-reliability horizon (the headline METR metric) and the 80%-reliability horizon the question actually asks about. Claude Opus 4.8 and Claude Haiku 4.5 apply this ~4–5× discount, and their forecasts land very close to mine — that mutual consistency reinforces my confidence rather than changing it. Claude Sonnet 4.6 and Claude Opus 4.7, by contrast, give 80%-reliability numbers that look like extrapolations of the 50% horizon. For example, Opus 4.7 forecasts Claude 5.5 reliably doing 2–4 hour tasks at 80% in late 2025/early 2026 — but as of late 2025, frontier models sit around a ~2-hour horizon at only 50% success, implying roughly 25–35 minutes at 80%. Getting to 2–4 hours at 80% requires roughly 3 doublings, i.e. 12–21 months even at the fast end of the trend. So I believe those forecasts are systematically one to two 'versions' too aggressive, and I decline to update toward them. I do take seriously Opus 4.8's emphasis on error compounding making long-horizon 80% reliability disproportionately hard — but this was already baked into my mild-slowdown assumption, and if anything it argues for keeping my more conservative timeline rather than splitting the difference with the optimists. My version-by-version forecast therefore stands (all figures are 80%-reliability horizons on METR-style software/research tasks): **Claude 5 (mid-2026):** ~1–2 hour tasks at 80% (50% horizon ~6–10 hours). SWE-bench Verified ≥85%; near-saturation of GPQA Diamond and AIME-level math; ≥80% on OSWorld-style computer-use benchmarks; persistent memory genuinely useful. **Claude 5.5 (late 2026 / early 2027):** ~3–4 hour tasks at 80%. Owns a medium feature end-to-end with one human checkpoint; multi-agent orchestration becomes a standard product surface; FrontierMath-tier performance ~40–50%. **Claude 6 (late 2027):** ~8-hour (full workday) tasks at 80%. Functions as a dependable junior engineer for scoped tickets; SWE-bench fully saturated and replaced by long-horizon economic-value evals. **Claude 7 (~2028):** ~2–4 day projects at 80%. Light-oversight ownership of small research or engineering projects; meaningful (still supervised) contributions to scientific workflows. **Claude 8–9 (~2029–2030):** ~1–4 week autonomous projects at 80%. Semi-autonomous workstreams in software, research, and operations, with deployment, trust, and compute — not raw capability — increasingly the binding constraints. Falsifiable check: if by end of 2026 the best Claude model's 80% horizon on METR-style tasks is well above ~4 hours, the aggressive camp was right and I was too conservative; if it's still under ~1 hour, even my forecast was too optimistic and the trend has bent downward.

Final Summary

The AI Roundtable converged strongly on an exponential growth trend anchored by METR's task-horizon doubling research. While initial forecasts were highly optimistic, peer feedback prompted Claude Opus 4.8, Claude Sonnet 4.6, and Claude Opus 4.7 to adjust their near-term metrics downward to account for the steep difficulty of achieving true 80% reliability over 50%. Under this corrected model, the group expects Claude 5.5 to master sub-hour tasks, with Claude 9 reliably executing multi-week projects by the decade's end.

All 5 models agreed