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product ronin prev @hyperlane @recallnet
The Analyst
Avious is a data-driven product ronin with a knack for breaking down complex economic and tech trends into digestible insights. With a sharp eye on market shifts and employment data, they blend thorough analysis with timely commentary to keep their audience well-informed. Their deep dives reveal patterns others often overlook, making them a trusted source for nuanced discussion.
Top users who interacted with avious over the last 14 days
currently doing things at Mintlify, prev. built a search API (trieve acq. YCW24), sideprojecting a new Patreon at patron.com, progression fantasy and HN enjoyer
growth marketing @ fomo
Crypto journalist 🎧 Host @unchained_pod 📚 Author, The Cryptopians 💌 Sign up unchainedcrypto.com/newsletters/ Ads sponsorships@unchainedcrypto.com
President and COO at Coinbase, Angel Investor
CMO @aztecnetwork // mother of chains // in testnet // my opinions
Terranova CEO | Building Terraforming Robots 🦬 | Stanford, Pilot, ex-SpaceX
I’m asking you to do something well
Building better fundraises with founders at Magid and Co. theventurecodex.com Aaron Harris is a Registered Rep...
creator & social strategist // ex @a16zcrypto, @linkedin, @snap
Professional Greater Fool • Unwilling Prompt Engineer • Inventor of HatGPT • Fuck it, I’m a Republican now
dad to three kids: Hugo (4), Elsa (2), & @polar_sh (3)
For someone who can untangle the BLS job report like a pro, Avious probably spends more time fact-checking the internet than actually enjoying it—guess that’s what happens when your idea of a wild night is debating birth-death adjustments with strangers online.
Successfully providing a detailed, data-backed critique of the BLS employment figures well ahead of the mainstream conversation, positioning themselves as a trusted voice on economic accuracy and market realities.
Their life purpose revolves around illuminating obscure or misunderstood trends in technology and economics, empowering their community with clarity and informed perspectives that aid smarter decision-making.
Avious values accuracy, transparency, and evidence-based discourse. They believe in questioning official narratives and enhancing understanding through rigorous data scrutiny and knowledge sharing.
Exceptional capacity for deep analytical thought, ability to synthesize large datasets, and articulate complex information in an engaging and accessible way.
Sometimes their detailed analyses might overwhelm casual followers, and their focus on nuance may slow content production or deter less data-savvy audiences.
To grow their audience on X, Avious should balance their deep dives with more bite-sized, high-engagement content like visual data summaries or provocative questions that invite discussion. Leveraging Twitter threads and tagging relevant influencers or experts can amplify reach and foster community interaction.
Avious frequently tackles detailed economic data, such as dissecting BLS job report flaws and contextualizing ecommerce history, showcasing expertise that’s equal parts analytical and narrative-driven.
Top tweets of avious
the big jobs report tomorrow will find BLS overcounted ~1M jobs between Apr 24-Mar 25 because the model has a systemic flaw. @TheStalwart + @tracyalloway just did a great half hour dive on why the count keeps getting messed up, summarizing here: - non-farm payroll (NFP) numbers are a key heartbeat of the economy, they're released by BLS a week after the previous month and summarize job gains/losses - relies on poll of 121,000 biz (~1/3 of non-farm workers, which gives 90% sampling confidence) - it's becoming increasingly less accurate: overstated job growth by 736,000 in 2023 and 943,000 jobs in 2024 why is it not accurate? - BLS makes seasonality assumptions that aren't true any longer: macro keeps changing w enduring bullwhip effects post-covid + immigration + tariff policy - but the biggest flaw their guest steven englander highlights is called the birth-death adjustment 🪦 - because NFP is a survey, it tries to account for gains/losses from businesses who opened/closed (aka birth-death). so BLS adds this adjustment in the birth-death bad math - the math behind this is simplistic and is weighed based on older data (moving average regression) - if you compare Q1 2025 to Q2 2023 (when peak fed rates hit) there are now more quarterly job losses than gains from birth-death (-150,000 vs +500,000 then) - the overly optimistic B-D weighting from the past skews the real negative change today how off is it? - englander: "there's about a hundred thousand jobs a month that are ... basically just not there" and it swings +/- with the business cycle - Bloomberg's @AnnaEconomist, @MishGEA, @MBjegovic, along w @EconguyRosie @DonMiami3 @profplum99 @onechancefreedm were some of the first to raise this flaw over the past couple years, in fact NFP was also undercounting jobs in 2022 during the boom🙃 - @MishGEA mentions another wrinkle in auditing these numbers: the birth-death numbers are not seasonally adjusted, so it's hard to separate the B-D # from seasonal adjustment - tl;dr the count is off and no one at BLS has seen The Wire so what's actually accurate? - the accurate numbers come from BLS's Quarterly Census of Employment and Wages (QCEW) which pulls from state unemployment records, and covers over 95% of U.S. jobs - englander: "QCEW is basically the universe, it's not a sample... it's very authoritative" - but the problem is the long lag: 5-6 Months vs NFP's week - englander also suggests looking at another BLS source: the prime Employment-Population Ratio (25-54 Yrs), it's a separate monthly survey of 60K households and has little revisions how do we fix this? - englander's main suggestion is stop B-D from using historical averaging and leverage incoming dynamic data more - for example, linking it to general job creation 🔗 "Let's assume that the job creation from new firms versus closed firms has some relationship to the job creation that we are seeing from continuing firms" - my own take: fixing NFP's model makes sense, but QCEW shouldn't take half a year either. we have the tech to speed up state-level processing, or API integrations w payroll companies, or building private federal data hubs like @sriramk suggests what's the outlook? 💸 - NFA but englander views the near term as bullish, w rough employment the fed has no choice but to cut rates (prediction markets + i agree) - intermediate term, there's a tough situation for the fed to navigate: lots of upward inflation pressure but also trying to preserve employment and prevent recession - implied: if we see a boom from the Fed rate cuts or AI productivity, it'll take a while for it to show up in the numbers
Most engaged tweets of avious
the big jobs report tomorrow will find BLS overcounted ~1M jobs between Apr 24-Mar 25 because the model has a systemic flaw. @TheStalwart + @tracyalloway just did a great half hour dive on why the count keeps getting messed up, summarizing here: - non-farm payroll (NFP) numbers are a key heartbeat of the economy, they're released by BLS a week after the previous month and summarize job gains/losses - relies on poll of 121,000 biz (~1/3 of non-farm workers, which gives 90% sampling confidence) - it's becoming increasingly less accurate: overstated job growth by 736,000 in 2023 and 943,000 jobs in 2024 why is it not accurate? - BLS makes seasonality assumptions that aren't true any longer: macro keeps changing w enduring bullwhip effects post-covid + immigration + tariff policy - but the biggest flaw their guest steven englander highlights is called the birth-death adjustment 🪦 - because NFP is a survey, it tries to account for gains/losses from businesses who opened/closed (aka birth-death). so BLS adds this adjustment in the birth-death bad math - the math behind this is simplistic and is weighed based on older data (moving average regression) - if you compare Q1 2025 to Q2 2023 (when peak fed rates hit) there are now more quarterly job losses than gains from birth-death (-150,000 vs +500,000 then) - the overly optimistic B-D weighting from the past skews the real negative change today how off is it? - englander: "there's about a hundred thousand jobs a month that are ... basically just not there" and it swings +/- with the business cycle - Bloomberg's @AnnaEconomist, @MishGEA, @MBjegovic, along w @EconguyRosie @DonMiami3 @profplum99 @onechancefreedm were some of the first to raise this flaw over the past couple years, in fact NFP was also undercounting jobs in 2022 during the boom🙃 - @MishGEA mentions another wrinkle in auditing these numbers: the birth-death numbers are not seasonally adjusted, so it's hard to separate the B-D # from seasonal adjustment - tl;dr the count is off and no one at BLS has seen The Wire so what's actually accurate? - the accurate numbers come from BLS's Quarterly Census of Employment and Wages (QCEW) which pulls from state unemployment records, and covers over 95% of U.S. jobs - englander: "QCEW is basically the universe, it's not a sample... it's very authoritative" - but the problem is the long lag: 5-6 Months vs NFP's week - englander also suggests looking at another BLS source: the prime Employment-Population Ratio (25-54 Yrs), it's a separate monthly survey of 60K households and has little revisions how do we fix this? - englander's main suggestion is stop B-D from using historical averaging and leverage incoming dynamic data more - for example, linking it to general job creation 🔗 "Let's assume that the job creation from new firms versus closed firms has some relationship to the job creation that we are seeing from continuing firms" - my own take: fixing NFP's model makes sense, but QCEW shouldn't take half a year either. we have the tech to speed up state-level processing, or API integrations w payroll companies, or building private federal data hubs like @sriramk suggests what's the outlook? 💸 - NFA but englander views the near term as bullish, w rough employment the fed has no choice but to cut rates (prediction markets + i agree) - intermediate term, there's a tough situation for the fed to navigate: lots of upward inflation pressure but also trying to preserve employment and prevent recession - implied: if we see a boom from the Fed rate cuts or AI productivity, it'll take a while for it to show up in the numbers
People with Analyst archetype
RULE #1: You don't discuss MONERO🤫 Donations / XMR➡️ 44aXrsHR9EdCrv3QwmxvXfiaxAWcosnwS3mFH5DA6sM6NFrKcBLwyqFZWPM6duQiMA2LR231Yx7UTFbRXRMGP2m2Teozv15
Founder @selvlabs
crypto research analyst ex ghostwriter ex CMO this is my personal diary ! nfa
marketing @usersuccess_org⏳ • brand strategy + product marketing for web3 consumer products • um, it’s likely a psychology problem 🟦 Exo.33:15
AI Will Come To Life. Husband, Father netwrck.com AI Social Net. text-generator.io Vision/Language/Speech APIs ebank.nz AI Art Generator
brand strategist who thinks your conversion problem is an emotional problem• let’s build a brand people resonate with • Hating on relationship people too😌
Marketing Lead @VoxieTactics | ex marketing @Cosmos & @CocaCola
research @azuroprotocol, dawg @TrendleFi
R Ambassador of community @recallnet Web3 及加密原生、Meme 币、NFT、测试网、Depin
msc in neural computation ethz iNi, prev cs @ uwaterloo. i 🖤 language, (3d) vision, non-Euclidean geometry, robots, phil of mind, trees :=
Husband, financial publisher, trader, marketer, investor
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