u/sholton1988

I work in GTM at a big tech company, and we're launching a new feature soon. Our ICP looks something like this:

-US fintech startups

-Series A–C

-30–150 employees

-Recently expanded into Canada

-Hiring their first Compliance or Risk Manager

-Doesn't already use enterprise compliance software

The main problem I've ran into is finding highly qualified leads (it’s been absolutely horrendous up until now). Spent 3 hours researching yesterday and ended up with 5 usable accounts.

At this point, I'd much rather pay a premium for a handful of highly qualified leads than keep paying for databases where 99% of the records are irrelevant.

I can't believe this is still the best way to do outbound in 2026…

When my kid was 4yo & I visited my Grandma's house with the kid. He was a crybaby. used to cry every time. I was so nervous at that time. I wanted to be the best mother & in that heat I was just messing things up. my grandma noticed it & Said - you dont have to be the best mother, you just have to be a Present mother. Your kid will appreciate that. I remember that till date after 5+ years.

What is your one such advice you received that you still with you over time?

I'm not arguing that AI is an environmental disaster, and I know the exact numbers around its resource use are still debated. That said, AI undeniably requires electricity, cooling, hardware, and water, and those demands will increase as it’s consumption continues to grow.

Saying that "other industries are worse" is absolutely not an argument. Every additional source of resource consumption contributes to the overall picture, even if it's not the largest one.

Like any fast growing technology, AI deserves to be evaluated for its environmental costs rather than dismissed simply because bigger contributors already exist.

And for the record, I'm already environmentally conscious, so "look at your own impact first" won’t work with me.

I found out two weeks ago that because I was over 29 while paying for Tinder Plus in California, I was eligible for a class action settlement over Tinder's age based pricing.

I got $180 but the average payout is actually even higher ($230 per person though it depends on how much you paid).

Don't wait too long if you're eligible, the claim deadline is August 18, 2026.

Here are the class action settlements to look out for in 2026.

• Google Assistant owned a Google Home/Nest Hub/Pixel (purchaser class, proof of purchase needed) OR used Google Assistant/lived in a household where it was used and had a conversation recorded via a "false accept" (privacy class, no proof needed), May 18, 2016–March 19, 2026 → est. $2–$56 depending on class → deadline Aug 27, 2026
• Amazon Prime enrolled through a deceptive signup flow or couldn't cancel online, June 23, 2019–June 23, 2025, used under 10 Prime benefits in any 12-month period, no proof needed → up to $51 → deadline July 27, 2026
• YouTube TV / DirecTV Stream (Disney) subscribed to either service, April 1, 2019–March 31, 2026, self-certify under penalty of perjury, no receipts → pro rata cash, amount TBD by subscription length and claim volume → deadline Sept 8, 2026
• Fanatics paid a handling fee on a fanaticscom order, May 6, 2018–March 30, 2026, no proof needed → two $5 vouchers ($10 total) → deadline Aug 27, 2026
• HSBC opened a direct savings account and made an ACH deposit via HSBC's online portal that wasn't credited interest same/next business day, March 25, 2014–Feb 20, 2021, unique ID from notice required → pro rata, minimum $10 → deadline Aug 20, 2026
• Shimano cranksets own/owned an affected Ultegra or Dura-Ace Hollowtech II crankset (pre-July 2019) AND replaced it before Sept 21, 2023 due to delamination/separation, after your original warranty had already expired → reimbursement of documented costs (receipts required, or a sworn declaration if you can't find them); extended warranty to July 29, 2027 is automatic, no claim needed → deadline Aug 4, 2026

Went through the Barclays summer internship process on campus for the 2026 batch. 134 of us were shortlisted for the assessment, 23 got selected, and I was one of them.

Online Assessment: 14 questions total: 1 DSA, 1 SQL, and 12 OOP MCQs across C++, Java, Python, and pseudo-code. The SQL question was a filter to display only October records, the LIKE operator was enough. The DSA question was a sliding window over two strings, asking for the smallest string of size L1+L2-1.

Interview Day (on campus): It opened with a pre-placement talk where 10 panelists introduced themselves. We were told there would be four rounds back to back.

Round 1 (about 40 minutes): DSA concepts, stacks, queues, arrays vs linked lists, merge sort, binary search, HashMaps. Then a walkthrough of my backend project, Firebase and data security, and one situational question on handling a security incident.

Round 2 (about an hour): project discussion with database schema design, DBMS joins, threads and processes, garbage collection, and the Producer Consumer problem.

At 4:30 PM they announced rounds 3 and 4 were cancelled. Round 2 was the final round.

Update (compared with the FTE candidates from the same season): Their loop went deeper: a SQL query joining three tables with a subquery, questions on GitHub contributions, and the full SDLC.

Sharing this because no post I found mentioned that rounds can get cancelled mid-day, and knowing that would have changed how I paced myself.

Can share more details in the comments if anyone wants them.

I've been thinking about trying one iMessage AI assistant. They seem like they'd be pretty useful for a lot of the stuff I'm trying to automate.

I know there's a bunch of them out there but the ones I see all over my fyp are Folk and Tomo. I'm not sure how they're different or what each one is best at.

Has anyone here used either of them and can give me some info ?

Basically, I switch between OpenClaw and Hermes Agent very often and can't even tell you the difference between both of them.

If there's some people that have spent a lot using either of them:

-Which one do you use the most, and why? -Are they built for different jobs, which one is better for what? -Does one hold up better under real use? -Does one of them have some extra features that the other one doesn't?

I’m trying to make a permanent decision because they have such different setups that I think it's making me way less efficient to switch between both all the time.

For context, I'm a software engineering student, and I use AI agents almost every day for coding, automation and my internship.

Any recommendation helps a lot. Thanks in advance...