Question to HN:

How many of you actually need the SOTA level intelligence of Sol and Fable? What kind of tasks do you use it for, and what did you do 6 months ago when SOTA models were as intelligent as today's B team?

The other day I tried a 31B model from a Canadian company and felt this is good enough for 80-90% of my tasks.

(For the cuorious: North Mini Code. Free on OpenCode/Zen right now. No affiliation :) )

For ordinary coding (making webapps, frontend and backend), the non-SOTA models do fine, but the SOTA models have better judgement and need me to intervene less often, allowing workflows like "Go and pitch me a solution to this problem, then go build it". 6 months ago, I would give lower-level tasks and read more of the code myself.

So I don't "need" the SOTA models, but they do help considerably. And I am also working on some other projects that may have been outside the reach of the earlier models entirely.

For the particular task I'm working on (a mathematical task in validated numerics), even Sol has generally just repeatedly given up. I asked it for the main problems it could not solve, gave them to Fable, and Fable solves them, every time.

There is a clear hierarchy here and Fable is well and truly at the top for very tough tasks. It just sucks that Anthropic is so incompetent at delivering a cost-effective experience without the uncertainty of it getting pulled. It doesn't matter how strong their model is, customers will turn away.

> What kind of tasks do you use it for

There are some bugs that just seem to elude Opus and GPT 5.5. An example is an Elixir/LiveView app that I wrote for personal use that basically gives me a full tmux in my browser from the system it's running on (very useful for VMs or when on-the-go on mobile and need to run a quick command or two). On mobile the scrolling is complex and janky and even Fable struggled to figure it out, even with me spoon feeding direction.

> what did you do 6 months ago when SOTA models were as intelligent as today's B team?

The bugs didn't get fixed. I tried, oh did I try. New bugs (worse than the one fix) introduced, other things breaking, etc. I just lived with the bugs or fixed them myself.

The sort of thing Fable and Sol excel at are long horizon tasks. The sort of thing I have been using them for is migrating large numbers of repositories to new tooling simultaneously (adopting new linters, enabling dependabot automerge, rolling out mutation testing).

Some of that can be done mechanically or trivially, and Fable knows to write a script or deploy Sonnet for those instances, but other times there are complications that need to be overcome that need to be escalated. Then there are patterns that can be picked up in large migrations and fed into template repos or tooling.

I won't use Fable for everything, but if there is ground to be broken on a new concept, being able to build a prototype with Fable might be useful.

I also have some substantive migration tasks such as replacing a static front end with solidjs or moving from NLL to Polonius that I would like to use Fable for.

It certainly feels like over the last fortnight it has enabled a substantial amount of transformative change in my codebases.

Plannig and review. You want the best plan and when its done you want to catch all the bugs. Implementation can be almost anything.

Of course you can do the planning and reviewing by hand but sota models do a pretty great job, especially in review (please still read the code).

ml research, both brainstorming and running experiments

eg I'd throw a hypothesis at it in the evening, and overnight it would write the code, do a sanity check, start a run, monitor the metrics, identify and fix a bug, propose a new hypothesis based on the results, write the code and start the second experiment, etc

still not that good at generating ideas or drawing conclusions, but much better at criticism than opus

even the api price is not that expensive for this

Personally I apply it every so often to audit codebases but it’s mainly sonnet and Gemini for most tasks. That and a harness for an agent to keep iterating on a goal is perfect. I’m more concerned buy getting hooked on the 50% increase on all models, not just Fable.

Fable is the first one I found could bring brainstorming concepts closer to what I was striving for instead of adding in clutter and defocusing.