MARKET RESEARCH
Tech Stack Shift Detector
Parses required skills from competitor engineering postings, detects when a rival starts demanding a new framework, language, or cloud, and opens a Linear issue for the research…
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled scan
- ActionScrape engineering postingsApify
- ActionExtract normalized tech list with LLMOpenAI
- ActionLoad competitor tech profile from AirtableAirtable
- LogicDiff stack, keep shifts above recurrence threshold
- ActionUpdate stored tech profileAirtable
- OutputOpen Linear issue for confirmed shiftLinear
What it does
It mines the requirements section of engineering job posts to fingerprint a competitor's technology direction. When a company that always hired for Java suddenly asks for Rust and Kubernetes, or starts listing a new data warehouse, that is a re-platforming signal worth understanding.
When to use it
Use this when technical strategy is your battleground, for example competing on infrastructure, data, or AI tooling. Product and engineering leaders use it to spot rivals' bets on stacks before those bets ship as features.
How it works
- 1A scheduled trigger runs the scan on a set cadence.
- 2Apify scrapes engineering postings from tracked competitors.
- 3OpenAI extracts a normalized list of technologies from each posting's requirements.
- 4The flow diffs the detected stack against the per-competitor technology profile stored in Airtable.
- 5A filter keeps only newly appearing technologies that cross a recurrence threshold, avoiding one-off noise.
- 6It updates the stored technology profile.
- 7For each confirmed shift it opens a Linear issue describing the change so an analyst can dig in.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect AirtableBases, tables, views, automations.
- 4Connect LinearIssues, projects, cycles, triage.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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