🍽️ Good food, good company. At the fire station, crews cook meals together and make time to prioritize good nutrition, even during busy days. But the kitchen is about more than the meal; the kitchen table is where crews slow down, sit together, and spend quality time with one another. It’s a place to share stories, joke around, talk through a tough call, vent, listen, and check in on each other. These everyday moments around the table build trust, strengthen connections, and create a space where people can let their guard down. It’s one of the many small things that make life at the station about more than just work. #CALFIRE# #StationLife# #Firefighters# #EngineCrew#

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Researchers engineered specialized yeast to transform discarded plastic into consumable cookies. A group based at Southern Illinois University Carbondale is addressing plastic pollution alongside food shortages through an unusual approach. Employing oxidative hydrothermal dissolution, the scientists apply heat to decompose used plastic bottles together with sweetcorn plant residues into forms that microbes can process. The resulting material is supplied to CRISPR-modified yeast strains that convert it into proteins, lipids, and a vanilla-like sweetness. After additional ingredients are incorporated, the blend is shaped via 3D printing into cookies known as µBites, redefining the idea of sustainable cuisine. Although the scientists are still seeking official clearance to sample the products themselves, the idea has generated both interest and doubt. Observers such as Jason Hallett of Imperial College London contend that producing food from plastic lacks commercial viability and cannot meaningfully address worldwide plastic accumulation, especially amid concerns regarding microplastics and genetic modification. The inventors counter that regardless of whether plastic-based cookies become commonplace, the work represents an essential advance toward reshaping societal responses to plastic refuse. [Jayakody, L. N. (2024). Next-generation 3D-printed nutritious food derived from waste plastic and biomass. Trends in Biotechnology, 42(6), 799–800. DOI: 10.1016/j.tibtech.2024.04.004]

i reverse engineered how supabase became the #1# recommended backend in AI search and where they're still losing 37.5% citation share. 99k github stars. $5B valuation. the default database for every vibe coding tool on the internet. when u ask chatgpt "firebase alternative with a SQL database" - supabase gets the blue link. "best managed postgres for a startup" - supabase. "add a database, auth, and storage to my react app without building a backend" - supabase. heres how they got there: > they built on postgres instead of inventing their own database. 30 years of trust, borrowed overnight. every developer already knows SQL. > they wrote comparison pages on their own site. "supabase vs firebase." "supabase vs auth0." "supabase vs heroku postgres." when someone asks the AI which backend to use, supabase has a page ready to be cited. > they invented "launch week" - every quarter they ship 5 major features in 5 days. 15 launch weeks so far. thats 75+ individual moments that each generate blog posts, backlinks, and content the AI trains on. > they shipped pgvector in early 2023, six months before most devs knew what a vector database was. by the time the AI wave hit, supabase was already the default answer to "where do i store embeddings." > they became the "connect to supabase" button in lovable, bolt, replit, and cursor. not because of deals. because supabase was already everywhere in the training data. but heres what blew my mind: supabase gets 0 citations on chatgpt for queries about their own core features: > "how do i make sure each user can only read their own rows in postgres" - this is literally row level security. supabase's signature feature. chatgpt doesnt cite them. doesnt even mention them. > "how do i push realtime updates to the browser when my database changes" - realtime is one of their 5 core products. 0 citations. > "how do i add google login and magic links to a next.js app" - supabase auth does exactly this. 0 citations. > "best vector database for a RAG app" - they shipped pgvector before almost everyone. 0 citations. qdrant and aws get cited instead. the pattern: supabase wins every query where someone names the category. but when someone describes the job they need done (the exact problems supabase solves) the AI has no page to link to. firebase is even wilder. mentioned 15 times across all queries but only cited twice. every AI knows firebase exists. none of them have a reason to link to it. supabase built one of the greatest developer platforms ever. and even they have blind spots in AI search. imagine what ur company is missing.

we reverse engineered how zapier became the #1# recommended automation tool in AI search 22% citation share. more than n8n and make combined. everyone talks about their google SEO (9M+ monthly visits). but heres what actually makes them win in AI search: > a dedicated page for every app integration combo. "connect gmail to slack." "connect stripe to airtable." 8,000+ apps means thousands of pages. when someone asks chatgpt "how do i automatically send form submissions to a google sheet and slack" zapier has an exact page for that. > they were first to frame automation as AI agents. zapier now leads with "AI agents and chatbots" not just "connect apps." when someone asks "tool to build AI agents that can use my existing apps" zapier gets cited #1#. > comparison pages they wrote first and control. "zapier vs make vs n8n" — they wrote it, they rank, they get cited on both chatgpt and gemini. > they turned integrations into a content moat. every new app that joins = hundreds of new pages = hundreds of new queries they can get cited on. chatgpt cited them on 6 out of 18 prompts. gemini on 3 out of 17. the playbook: they didnt just build the most integrations. they made sure every integration had a page the AI could cite. 8,000 integrations = 8,000 answers to questions ppl ask chatgpt.