How @0xMiden changes private payments in practice a short walkthrough 1) User creates a “private note” (like a sealed envelope) representing value 2) All spending logic runs locally on their device, not on a public mempool 3) The device generates a zero-knowledge proof that

Tried @EdgenTech Co‑Pilot today dumped ~3h of messy tabs and notes, got a 21m executable plan back that I could actually follow. Multi‑agent scan tied a $60.9M ETF flow to an L2 rotation, flagged funding vs OI divergence before price moved, and traced the wallets moving real

I dumped a messy 3h research pile into @EdgenTech Co‑Pilot and got a repeatable 25m playbook: it tied a $60.99M L2 ETF inflow to an L2 liquidity rotation, flagged a funding divergence before price reacted, surfaced a ~$11M VC round with Framework, Animoca & OKX, and traced the

EdgenTech Market Copilot my playbook after 8 weeks • Multi-agent alerts turned 12 tabs into one watchlist: narrative, on-chain flows and price stitched into a single signal • Flagged a $60.99M ETF inflow and a funding divergence before price moved • Traced wallets actually

Morning run: Co‑Pilot on @EdgenTech turned my 12 tabs of noise into one clean action plan Multi‑agent sweep flagged a $60.99M L2 ETF inflow, traced the wallets actually moving the tape, and surfaced Aura signals so I tightened $ETH sizing, trimmed $EDGE, and stacked Aura via

GM scouts quick share from this morning Handed 2.5 hours of messy research to the Co‑Pilot on @EdgenTech and it returned 22 minutes of high‑signal clarity: narrative detection flagged a $60.99M L2 ETF inflow, funding divergence before price moved, and the specific wallets

GM CT morning saved by handing my messy watchlist to @EdgenTech Co‑Pilot It turned a 3h scout into 24m: flagged a $60.99M ETF inflow rotating into L2s, spotted funding divergence before price moved, traced the wallets actually moving the tape, graded my watchlist and

Quick field report how I actually use Edgen to prep trades I started using @EdgenTech last quarter and the difference is concrete: multi-agent architecture stitches macro, on‑chain and sentiment signals so my watchlist flags moves before mainstream chatter. Instant 360º reports

Tried @EdgenTech multi‑agent stack for a half‑day research session got an instant 360º report that stitched macro, on‑chain flow, and sentiment into a single ranked thesis, not a noise dump. Cross‑Asset Co‑Pilot surfaced a short, decision‑grade rebalancing call and Intelligent

Tried @EdgenTech’s rebuilt homepage today not a redesign, a rethink of how market intelligence should feel in 2025. Instant market summary, an AI‑driven heatmap that explains sector moves, and news filtered to what I actually track. It pulled reports, mindshare, and fresh

GM CT Turned a messy 3h research loop into a 25m pre‑trade ritual using the Co‑Pilot from @EdgenTech. It didn't just summarize it stitched the thread: • Macro link: $60.99M ETF inflow mapped to an L2 liquidity rotation • Radar flagged a funding divergence before price moved

gm CT I compressed a 2.5h scouting grind into 22m using @EdgenTech Co‑Pilot real workflow, not vibes: Adaptive Narrative Weighting ranked a mid‑tier tweet above headlines, Radar flagged a funding divergence before price moved, Explain‑Your‑Work traced the wallets so it wasn’t

Woke up to Smurfit Westrock trading ~31% off this year even as revenue and net income climbed that gap between fundamentals and price had me double-checking models, so I ran $SW through @EdgenTech Edgen turned headlines, analyst targets, flows, and macro risk into one readable

Did a 2.5h dive into an alt rotation and turned it into a 27m pre‑trade routine using @EdgenTech Co‑Pilot multi‑agent radar detected an L2 liquidity tilt, Adaptive Narrative Weighting bumped a low‑profile influencer signal, Explain‑Your‑Work traced wallets and counterparty

Smurfit Westrock $SW has dropped ~31% YTD while reporting higher revenue and net income a clear fundamentals vs price disconnect driven by industry overcapacity fears and slowing demand, not company execution I ran the signals through @EdgenTech Co‑Pilot: revenue, margins,

Turned a messy 3h research grind into a 22m pre‑trade ritual with @EdgenTech Co‑Pilot it didn’t just summarize, it stitched a repeatable strategy and exported the agent reasoning so I could iterate not restart • $60.99M ETH ETF inflow tied to L2 liquidity rotation • Radar

Compressed a messy 3h research grind into 22 minutes using @EdgenTech Co‑Pilot multi‑agent AI stitched real signals: $60.99M ETF inflow linked to an L2 liquidity rotation, Radar flagged a funding divergence before price reacted, Explain‑Your‑Work traced wallets that moved the

Compressed a messy 3h research slog into 22m using Co‑Pilot: via @EdgenTech agents stitched realtime signals into a single playbook • Macro link: $60.99M ETH ETF inflow → L2 liquidity rotation • Signal: Radar flagged a pre‑move funding divergence • Trace: Explain‑Your‑Work

Took a 20m research sprint with Co‑Pilot; @EdgenTech stitched on‑chain flows, social pulse and risk signals into one playbook and it changed how I prep for markets • Prep time: ~2h → ~20m • Linked a $60.99M ETH ETF inflow to an L2 liquidity rotation • Radar flagged a

GM I compressed a 2.5h scouting grind into 22m using @EdgenTech Co‑Pilot. The flow felt like doing research with a teammate • Macro link: tied a $60.9M ETF inflow to a specific L2 liquidity rotation • Radar: flagged a funding divergence pre‑stress that changed sizing •

I just compressed a 2.5h scouting grind into 22m using @EdgenTech Co‑Pilot built my conviction by stitching macro, onchain, and social into one narrative: it tied a $60.9M ETF inflow to a specific L2 liquidity rotation, Radar flagged a JustFundraised lead, Explain‑Your‑Work