AWS for Software Companies Podcast

Nexthink’s journey from on-prem to cloud to AI-native shows how two decades of endpoint data, Amazon Bedrock and rigorous evaluations power Spark, an autonomous agent that is reshaping the service desk.

Topics Include:

• Nexthink: two decades turning workplace IT failures into fixable signals.
• Monitoring 25 million endpoints, processing gigabytes of real-time signal per second.
• AI-native revenue jumped from $20M to $109M in one year.
• Rewriting every line of code to go from on-prem to cloud.
• Why cloud transformation is about culture and mindset, not just technology.
• Remediation and workflow engines running billions of fixes at scale.
• How ChatGPT's arrival sparked an AI lab to reinvent the company.
• Six months of prototyping that became an autonomous IT agent.
• Every enterprise shares one lasting problem: technology will eventually fail.
• Employees suffer first, work around issues, and rarely report them.
• Giving IT visibility and tools to fix problems before tickets pile up.
• Why data and context, not frontier models, are the real moat.
• "Teams is slow": what generic AI guesses versus what telemetry knows.
• Why everyone hated chatbots: they routed tickets instead of solving problems.
• Spark's success metric: resolve in minutes, escalate only when necessary.
• Grounded in device data, Spark knows more than you tell it.
• Eyes on the problem, hands to fix it, with permissions respected.
• A hotel-room VPN failure diagnosed from a single screenshot.
• Inside troubleshooting mode: hypotheses, diagnostics, and an audited fix in seconds.
• Why Amazon Bedrock enabled a model-agnostic, multi-model strategy.
• When to stick with foundation models and when to fine-tune.
• The harness: where most agent engineering time actually goes.
• Evaluations from day zero: never ship changes on intuition.
• "Let the LLM reason, let the data decide."
• Treating AWS as an engineering partner, not a supplier.
• Scaling Amazon MSK from 5 to roughly 15 gigabytes per second.
• Will the service desk as we know it survive five years?
• Customers reporting 70% resolution rates and 40% ticket deflection.
• A broken-monitor fix that uncovered hundreds of employees with the same unreported problem.
• An email distribution list request handled by Spark in minutes.

Participants:

• Moe Haidar: Head of Agentic AI Engineering (Spark AI), Nexthink
• Kamil Davidov: Sales Leader, Israel ISV-BizApps, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

See how enterprises run AI in production on AWS, from frontier models on Amazon Bedrock to Amazon Bedrock AgentCore for governing, securing and tracing agents across every system

Topics Include:

• Why software breaks into five layers: persona, interface, logic, platform, data.
• AI is changing who uses software and how they interact with it.
• Workflows are breaking out of single SaaS tools and running across multiple providers.
• Zero-copy data access unlocks insights trapped in separate departments.
• One AI surface replaces three logins across Salesforce, SAP and Adobe.
• Governing agents: trusted registries, cost controls and token management.
• Security has to run at machine speed when vulnerabilities surface daily.
• Tracing and evaluating workflows that hop between different systems.
• Margin compression: what token costs do to the economics of AI products.
• Four pricing models, and why seats-plus-tokens hybrids are winning.
• Embed, extend, expand or create: a two-by-two grid for AI products.
• Real examples: Intercom Fin, Slack AI tiers, Workday HiredScore.
• First mover or fast follower? AI-built PR FAQs speed up product decisions.
• Why roughly 70% of developer time isn’t spent coding.
• MCP as the new TCP/IP for multi-vendor agent ecosystems.
• Why non-technical salespeople are quickly embracing AI interfaces.
• The four layers: AI surface, harness, reasoning models and chips.
• Why context and memory in the harness make or break agents.
• Building for security, scale and open standards across the AI stack.
• Will models eat the harness? Data and context take centre stage.

Participants:

• Mahdi Sajjadpour – Director, Solutions Architecture, Strategic ISVs – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Front CEO Dan O’Connell explores whether customer experience should be AI-first or human-first, and why unifying siloed teams onto a single platform transforms the customer experience.

Topics Include:

• How customer-facing teams manage complex relationships across email, chat and voice
• From headsets and green screens to today’s modern customer service
• The defining question: AI-first or human-first customer touch points?
• Why siloed support, success and sales tools fragment the customer experience
• Automation versus experience: deciding what your customers actually want
• Why experimenting with AI now protects you from faster competitors
• Customer support’s clear metrics make it prime territory for AI ROI
• How a shared inbox idea evolved to suit an agentic world
• Unifying support, account management and customer success in one place
• A logistics workflow turning plain-text emails into app-like quote comparisons
• Seamless handoffs between AI agents and humans on a single platform
• Why email and voice are critical infrastructure where downtime costs revenue
• Scaling from startup credits to enterprise without a major rewrite
• Moving upmarket and why customers’ cloud commitments matter
• Bringing telephony into the unified thread via Amazon Connect
• Is voice dying? Generational and company-size differences explored
• Why AI adoption moves at different speeds outside Silicon Valley
• Choosing AI models: balancing quality, latency, price and innovation
• The ultimate test: not knowing whether a human or agent helped
• Spotting the warning signs: teams coordinating problems instead of solving them

Participants:

• Dan O’Connell – Chief Executive Officer, Front
• Matt Rivron – Account Manager, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

LaunchDarkly CPO Jonathan Nolen breaks down how teams can build, validate, and ship software at agent speed, without losing control.

Topics Include:

• Jonathan Nolen explains how LaunchDarkly helps 3,000 enterprises manage change.
• Target features down to individual users and toggle them without redeploying.
• Customers range from startups and government agencies to airlines and pizza delivery.
• Why LaunchDarkly sells cultural change, not just a developer tool.
• Engineers are creatures of habit, so adoption takes real evangelism.
• Instant rollback means you hear about incidents next morning, not at 2 a.m.
• We’re living through a rebirth of the software development lifecycle.
• Ramp is building its own software factory powered by autonomous agents.
• A healthcare insurer is building its agent factory on just three tools.
• Start agents on bug fixes, then features, then whole projects.
• Why Nolen is retiring the term “vibe coding.”
• Code written at agent speed must be validated at agent speed.
• There are two levers: invest in testing, or shrink the blast radius.
• Progressive rollouts move from internal users to synthetic tests to beta cohorts.
• No single safeguard is enough; layered techniques build real confidence.
• The key metric is valuable software shipped per unit of human attention.
• Automate everything, and bring humans in only where judgment matters.
• LaunchDarkly is on the same AI journey as its customers.
• Why LaunchDarkly sees itself as critical infrastructure, not just SaaS.
• It designs for failure, so customer apps keep running during outages.
• Two questions to ask: how fast, and how granularly, can you fix releases?
• Big-batch rollbacks hold every team captive to the slowest feature.
• Turn off just the broken feature, fleet-wide, in under a second.
• Nolen’s biggest recent lesson: first ask AI how to solve the problem.
• Inside LaunchDarkly’s culture: one team that wins or loses together.
• Ownership, smart bets, and using risk to your advantage.
• Radical transparency means less time spent agreeing on what reality is.
• Cheap code creates new bottlenecks, like humans trying to review everything.
• The future is learning by building and testing ideas directly in production.
• The organizations that close this loop fastest will see compounding advantages.

Participants:

• Jonathan Nolen – Chief Product Officer, LaunchDarkly

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Discover how Veeva transformed a free clinical research platform into a sustainable freemium business, balancing with their mission through transparent communication, fair pricing, and smart migration tooling built on AWS.

Topics Include:

• How Veeva builds industry cloud software for clinical research sites
• Why clinical trials sit between healthcare delivery and life sciences
• How a free platform grew into a self-sustaining business
• Balancing monetization and mission: free tiers, fair pricing, annual true-ups
• Giving 15 months' notice and over-communicating the why
• Building migration tooling to move users from multi-tenant to enterprise
• Handling edge cases and migration issues through radical transparency
• Navigating customer pushback amid 2025 NIH funding cuts
• What a strategic AWS partnership looks like beyond infrastructure
• Getting more from AWS by sharing long-term goals, not transactions
• Advice for SaaS leaders: set boundaries, prioritize fairness, own the message
• Preparing teams for change without gaming out every objection

Participants:

• Nick Frenzer – General Manager, Site Solutions, Veeva

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Go inside a massive, still-in-progress migration of 1,500+ servers out of two Canadian data centers, with candid lessons on what works, what was surprising, and what to do differently.

Topics Include:

• Inside a live migration: 1,500+ servers leaving two Canadian data centers.
• How BlackBerry became a secure communications and QNX vehicle software company.
• Decades of legacy systems, and why standing still became costlier.
• Three converging forces: VMware licensing, hardware end-of-life, and FinOps gaps.
• The goals: close data centers, exit VMware, modernize only what matters.
• Choosing partners and funding programs that work as one team.
• A five-week assessment with parallel workstreams and five key workshops.
• Rehost, re-platform, or refactor: pragmatism over migration ideology.
• Early lessons on discovery, cost transparency, and over-communicating.
• Building the landing zone: accounts, networking, identity, and security.
• Discovery, right-sizing, then migrating, validating, and cutting over workloads.
• Wave planning: start simple, save the most complex workloads for last.
• Day two: cost tagging, observability, and AI-assisted modernization backlogs.
• Final advice: business case first, migrate now, modernize later.

Participants:

• Jason Whissell – Vice President, IT & Business Application Solutions, Blackberry
• Mehran Najafi PhD - Principal AI Architect & Head of AI Solution Architects, AWS Canada, Amazon Web Services  

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

From data-center chaos to billion-dollar acquisitions: the real story behind Clio's cloud journey, compliance battles, and rapid AI-driven transformation.

Topics Include:

• AWS-Clio partnership: migrate, modernize, add AI, then co-sell
• Legal industry ran on WordPerfect, mainframes, and homemade billing
• Clio launched 2008, same year as AWS's first database
• Now serves 400,000+ legal professionals across 130 countries
• Landed legal tech's largest-ever acquisition, raised $500M Series G
• Ships code 50-100 times daily in a regulated industry
• Started split across a data center, Azure, AWS, some GCP
• Nine years of acquisitions, fundraising, and rapid team growth
• Sharded databases, added regions for compliance and low latency
• Engineering team grew from 40 to over 650 people
• Lawyers once feared cloud security and data ownership questions
• Three principles: data security, system resilience, data regionality
• Stage one: survival, learning EC2, RDS, S3 basics
• Stage two: earning trust through SOC 2, PCI compliance
• AWS became a compliance partner, not just a host
• Stage three: AI reshapes coding speed and company culture
• Integrating acquisitions scattered across Heroku, GCP, Azure, others
• VLUX deal added a billion-document legal case-law database
• Rapid acquisition-to-launch playbook: some products shipped in days
• Strategy: avoid single AI vendor, preserve maximum optionality

Participants:

• Jonathan Watson – Chief Technology Officer, Clio
• Martin Bazinet – Director of Technology, AWS Canada, Amazon Web Services  

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Experts from Pegasystems and AWS reveal how AI-powered tools now modernize decades-old mainframe systems in weeks instead of years—unlocking trapped data faster than ever.

Topics Include:

• Session covers accelerating mainframe modernization using AWS Transform and Pega Blueprint
• Agenda: challenges, joint solution, value prop, customer story, rollout mechanism
• Mainframe costs rise 20-30% yearly, straining IT budgets significantly
• Monolithic systems create long time-to-market, hurting competitiveness against newer rivals
• Mainframe data stays locked away, blocking AI adoption and innovation
• Retiring mainframe skills outpace new workforce training, compounding the problem
• AI now enables analyzing decades-old code bases within weeks, not years
• AWS Transform extracts business logic; Pega Blueprint visualizes modernized target applications
• Five-step journey: Transform, Pega Foundry, Blueprint, then deployment via Infinity platform
• Three Transform agents handle code, data, and activity analysis separately
• Data analysis covers data lineage and data dictionary schema extraction
• Outputs feed a knowledge graph, enabling natural language queries anytime
• Transform deterministically identifies distinct data paths from mainframe systems
• Data paths get grouped into business functions, each modernizable independently
• Final steps extract business logic and generate plain-English requirements
• Blueprint agent enriches Transform outputs, enabling intuitive workflow design
• Blueprint offers runtime previews and is publicly accessible at pega.com
• Pega Infinity platform handles both batch and online mainframe workloads
• Insurance company Unum modernized 1.5M lines of COBOL in three months
• Experience-Based Acceleration program delivers modernized, working code within four-to-six weeks

Participants:

• Surender Kumar – Director, Mainframe Modernization, Pegasystems
• Ujwal Bukka – Sr Partner Solutions Architect, Business Apps, Amazon Web Services
• Sourav Sarkar – Sr Worldwide Specialist Solutions Architect, Mainframe & Legacy Modernization, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Discover how Zuora turned its own billing platform inward to track AI costs down to the individual engineer, giving CFOs the trust and auditability they demand.

Topics Include:

• AWS's Achint Naveen opens, introduces Zuora as a key partner
• Audience poll reveals AI monetization is still a struggle
• Zuora's Katherine Shealy introduces the company's AI monetization focus
• Zuora powers monetization for global brands like Twilio, Zoom
• Their platform spans CPQ, billing, metering, and revenue recognition
• Usage-based pricing has flipped seat-based SaaS models upside down
• AI companies face a 20-point margin gap versus SaaS
• Companies juggling multiple pricing models face major hidden complexity
• Traditional pricing models are breaking down under AI's dynamic costs
• Zuora's framework aligns teams early through an NPI-style process
• Their tech lets companies iterate pricing at engineering speed
• Zuora now tracks its own AI costs internally too
• Zuora AI runs on AWS Bedrock and AgentCore infrastructure
• AWS's Achint details the full stack behind Zuora AI
• AgentCore Memory gives Zuora's agents secure, persistent context

Participants:

• Katherine Shealy – Principal Product Marketing Manager, Zuora
• Achint Naveen – Sr Account Manager, Amazon Web Services  

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Sophos CSO Simon Reed reveals how attackers now operate like leveraged businesses—and how AI is making both sides of the cyber arms race dramatically more sophisticated.

Topics Include:

• Intro: Simon Reed, CSO at Sophos, joins Kamil Davidov.
• Sophos defends 625,000+ organizations with AI-native Fusion platform.
• Sophos MDR runs the world's largest agentic SOC.
• Simon's journey: cybersecurity since 2001, from graffiti to warfare.
• Cyber threats framed as constant toxicity, not occasional lightning strikes.
• Sophos spans small business to enterprise, giving unique threat visibility.
• Attackers now operate as leveraged, ecosystem-driven businesses, not lone actors.
• AI dramatically increases attack quality, speed, and sophistication.
• AWS Local Zones cut latency for Sophos's threat intelligence cloud.
• IntellX connects every product to real-time global threat data.
• "Good day" means finding novelty before attackers exploit it.
• Worst days: sudden, unpredictable supply chain compromise scenarios.
• Sophos updates protection across 600,000 customers within minutes.
• Decisions made fast, on incomplete data, balancing speed and risk.
• Sophos has pursued AI and deep learning for eight-plus years.
• Agentic AI's next phase reduces laborious human security work.
• Simon prioritizes class-based, automation-scale defenses over budgets.
• Sophos cut data platform costs 30%, migrated ahead of schedule.
• Advice: hyper-engage AWS account teams, push for more.
• Closing story: Sophos helped stop ransomware hitting hospitals during COVID.

Participants:

• Simon Reed – Chief Security Officer, Sophos
• Kamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/