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Amos Elliston liked thisAmos Elliston liked thisThe SDR role is rough. – 100+ dials a day – 2% connect rate – Rejection after rejection So why do so many college grads sign up for it? Because the SDR role is a fast track to become an AE. At least, in theory. In reality, most SDRs never get the chance to prove they can: – Run a full demo – Navigate pricing objections – Negotiate – Close They constantly lose out on promotion opportunities to external candidates. Instead of forcing SDRs to prove themselves in the interview process, forward-thinking sales teams are using AI Roleplay to certify their top SDRs can handle the conversations AEs need to master. Here's the outline of a recent program we designed with one of our clients: Level 1: Discovery Level 2: Value Translation Level 3: Objections Level 4: Negotiation Level 5: Account Management Want to implement it in your company? Comment "program" and I'll send you the full 20-page program breakdown.
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Amos Elliston liked thisAmos Elliston liked thisBanking, payment acceptance and credit cards, all in one place.
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Amos Elliston liked thisAmos Elliston liked thisHow to work 9-9-6 with 2 small kids (and not get a divorce). I’ve been waiting for someone to write this post. But, of course, anyone working 9-9-6 with kids has zero time to write it. So I thought I’d give my personal take: With kids you can't really work a strict 9-9-6. But it ends up looking like a similar number of hours. I'm often up at 4a responding to emails until I hear our 2 year-old on the monitor demanding a morning baba. I end up working most Saturdays (we get childcare) and try hard not to work on Sundays. Most weeks I wish I could spend more hours working and more hours with family. But we live in a world of trade-offs. There are only 168 hours in a week. I try to remind myself that it’s a privilege to have even one thing you want to pour yourself into, let alone two. Some quick advice for making the most of your working hours: – Prioritize work that’s in your zone of genius – Learn to delegate the stuff that isn’t – Spend more time on making decisions to avoid wasting time – Get comfortable saying “no” to things that don’t move the needle For family hours, try really hard to be present. Bring your best self to those hours and intentionally savor them. You probably won’t get it perfect, but you can make peace with the tension.
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Amos Elliston liked thisAmos Elliston liked thisIt was almost exactly one year ago that Sean Linehan and I launched AI Roleplays. For the last decade, I’ve listened to leaders talk about how they wanted better-trained people and then underinvest in training. I used to think they weren’t being rational. But, over time, I came to understand: They wanted the outcome of training (behavior change) but didn’t believe the existing modalities of training would deliver. And they were right. Every training modality used to come with show-stopping tradeoffs: On the one had you have activities like human role play which are effective but hard to scale. On the other hand you have things like content, which are easy to scale but don't move the needle on true skill development. So we started asking a different question: Where does training actually work? We looked at the Olympics, the CIA, fighter pilots– all places where training tends to work well. And it’s because they have a few things in common: 1. A practice environment that's almost indistinguishable from the performance environment 2. Fast feedback loops with expert coaches and trainers 3. Spaced repetition to build skills that become second nature It became clear to us, that someone needs to build the flight simulator for conversation-based training. Yesterday, we landed our third 300,000+ employee organization. When Sean originally demoed Roleplays to their CEO he said, "man every customer-facing employee in our company should be using this." Exciting to see the vision becoming a reality.
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Amos Elliston liked thisAmos Elliston liked this80% of our code is now written by AI... ...But humans are 100% accountable for it. I don't care if engineers… - copied it from Stack Overflow - copied it from GitHub - or an AI wrote it The engineer is accountable for 100% of the lines of code they ship to production. Sure, AI can write code FOR you. But you still have to understand every line. You still have to be responsible for every function. You still have to own the outcome. "The dog ate my homework" isn't an excuse in the AI era. Most people on my team are basically managers of LLMs now. But being a manager means you're accountable for everything your reports produce. Same principle applies here. AI writes fast. Humans own forever.
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Amos Elliston liked thisAmos Elliston liked thisGreat managers act like engines of economic mobility. They know their people’s strengths and weaknesses, carve out roles where they can thrive, and help them turn that impact into higher compensation and bigger opportunities. This doesn’t happen by luck. It happens because those managers have built skills like active listening and coaching to motivate people to do their best work. Skills like that can be trained, practiced, and scaled. Just requires an organization with the shared commitment.
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Amos Elliston liked thisAmos Elliston liked thisI see one, consistent mistake over-and-over: mission creep. The great employee who keeps getting piled with more goals, each pulling them in a new direction. Eventually, they fail to deliver on all of them. Mission creep kills your team’s performance. What happens when you tell your team to work on… - Their core role - Three other roadmap initiatives - As well as coaching and mentoring new hires They’ll end up: - Being pulled in multiple directions - Doing them poorly at a surface-level - Feeling bad about their performance But when you give someone one clear target: They're not balancing conflicting goals. Or context-switching between parallel priorities. They're just executing on one mission… Exceptionally well.
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Amos Elliston liked thisAmos Elliston liked thisWe’re training a client’s enterprise sales team on discovery calls. Right now, they’re consistently landing 5-figure deals. It's clear that path to 6- and 7-figure opportunities is going deeper in discovery. Not just finding ANY pain. Finding THE pain the business will pay a lot to solve. 𝟱-𝗳𝗶𝗴𝘂𝗿𝗲 𝗽𝗮𝗶𝗻: “It takes way too long to do this with our current systems.” 𝟲-𝗳𝗶𝗴𝘂𝗿𝗲 𝗽𝗮𝗶𝗻: “We’re losing customers and top talent because of this.” 𝟳-𝗳𝗶𝗴𝘂𝗿𝗲 𝗽𝗮𝗶𝗻: “We’re losing market share and we may not be able to get acquired if this doesn't get fixed.” Our prescription: Practice discovery role-plays where sellers… 1. Move past workflow pain (5-fig) 2. Identify business impact (6-fig) 3. Elaborate to massive opportunities and existential risks (7-fig) Same prospects. Same problems. Just deeper discovery and bigger deals.
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Amos Elliston liked thisAmos Elliston liked thisManagers today handle 10-20 team members. At the scale, it's near impossible to effectively coach all of them while: Managing up - reporting to their own bosses Producing reports - creating analytics and status updates Running processes - being accountable for operational deliverables So companies have two choices: 1. Hope employees don't really need the coaching (they do) 2. Or build infrastructure that scales coaching without more managers (they should) If you choose #2: Build technological infrastructure that handles the systematic stuff: - skill assessment - practice scenarios - feedback delivery - progress tracking This frees managers to focus on what only humans can do: - Find what personally drives each individual to get better - Know when someone is overwhelmed and adjust expectations - Help them navigate unwritten rules, office politics, and cultural sensitivities AI technology can scale the systematic coaching work. So humans can excel at the messy, contextual, relationship-driven work.
Experience & Education
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Publications
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Na Kika: Secure Service Execution and Composition in an Open Edge-Side Computing Network
USENIX NSDI '06
Making the internet's edge easily extensible fosters collaboration and innovation on web-based applications, but also raises the problem of how to secure the execution platform. This paper presents Na Kika, an edge-side computing network, that addresses this tension between extensibility and security; it safely opens the internet's edge to all content producers and consumers. First, Na Kika expresses services as scripts, which are selected through predicates on HTTP messages and composed with…
Making the internet's edge easily extensible fosters collaboration and innovation on web-based applications, but also raises the problem of how to secure the execution platform. This paper presents Na Kika, an edge-side computing network, that addresses this tension between extensibility and security; it safely opens the internet's edge to all content producers and consumers. First, Na Kika expresses services as scripts, which are selected through predicates on HTTP messages and composed with each other into a pipeline of content processing steps. Second, Na Kika isolates individual scripts from each other and, instead of enforcing inflexible a-priori quotas, limits resource consumption based on overall system congestion. Third, Na Kika expresses security policies through the same predicates as regular application functionality, with the result that policies are as easily extensible as hosted code and that enforcement is an integral aspect of content processing. Additionally, Na Kika leverages a structured overlay network to support cooperative caching and incremental deployment with low administrative overhead.
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