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Fig

Experimenting with long horizon prediction for personhood

Details

External ID
46827904
Source
HN
Company
—
Product
Fig
Website domain
figcareer.com
Launched
Jan. 30, 2026
Cohort
—
Upvotes
6
Upvotes percentile
0.2549407114624506
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hey HN,We explored how decision-making happens under severe information asymmetry and used career exploration as a test subject. In practice, people converge on a small set of highly legible default paths, with little visibility into credible alternatives.That’s why we’re building Fig, a tool for reasoning about career paths when the next step isn’t obvious, given the dependence on fleeting personal preferences.Most existing tools respond by collapsing uncertainty into a single recommendation or by modeling careers as linear trajectories. That works reasonably well at the recruiting stage, but fails earlier, during discovery, when paths are nonlinear and highly path-dependent. At that stage, the challenge is understanding which sequences of moves are even plausible.Fig is built for that gap. It treats career exploration as a reasoning problem rather than a prediction problem. The system builds context from multiple signals, including structured data like résumés and work history, alongside behavioral signals such as long-form content people actually engage with (for example, YouTube watch history related to skills or domains of interest). These inputs are grounded in observed career transition data to generate and compare multiple plausible trajectories, instead of producing a single “best” answer.Fig helps users reason about what they could do, given their current state, constraints, and how different choices tend to compound over time.You can try it here: https://figcareer.comWe’d appreciate feedback on whether this framing is useful, where it breaks down, and what additional signals would make long-horizon decisions easier to reason about.Happy to answer questions!

Enrichment

Theme
indie hacker passion projects
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
long horizon prediction model
Manually corrected
False

Could you build this?

Partial The UI for career exploration is simple, but constructing accurate probabilistic career trajectories and long-horizon outcome simulations requires proprietary longitudinal data and specialized statistical modeling.

What it would actually take: Requires a rich longitudinal career dataset (e.g. millions of scraped LinkedIn profiles or labor statistics), a vector search/graph DB for career transitions, and predictive recommendation models to simulate alternative trajectories and probability distributions under sparse data.

Discussion

2 comments analyzed.

Concerns raised: Unrealistic career path suggestions (CTO after 2 years), Unclear how YouTube history and chat data influence recommendations, Suggestions appear derivable from resume alone without added value from extra inputs

Feature requests: Better calibration for career progression timelines, Transparency on how different data sources impact suggestions

Competitors

Other products that read as similar to this one — 147 launches clear the similarity bar, closest 8 shown.

Attention rank: #117 of 148 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 90 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.