Positioning thesis: "Energy regulation, built into product." The archive shows a candidate who has already begun executing this pivot — but whose public footprint and network aim have not yet caught up with his intent.
Read chronologically, your Positions, Education, Certifications and Projects files describe a single transmission line stepping up in voltage: practice → platform → regulator. Each role feeds the next; nothing is a detour once the line is drawn. The risk is that an admissions committee reads the raw profile, not the line.
"A strong Indian media/IP litigator who tried a legal-tech side project and recently took a government research job." Evidence they'd anchor on: headline still reads "Building Tech-Enabled Access to Legal Recourse", industry field = Legal Services, your 6 lifetime posts are all media-and-entertainment law, and your most-endorsed skills are Copyright Law, Compliance Management, Trademarks (3 each). LinkedIn's own ad model job-titles you as "Legal Associate / Senior Associate / Legal Specialist."
"I've spent 7 years learning how rules become products: enforcing IP rules for $50M media deals, then compiling 25,000+ regulations into a working consumer platform (Equalaw), and now writing the rules themselves at India's apex power regulator. An MBA converts that into the person who sits inside a renewable-energy platform and translates tariff orders and market design into roadmap." Every clause above is sourced from Positions.csv / Projects.csv — the arc exists; it just isn't told anywhere public yet.
Classification by keyword + curated company lists over the Company and Position fields (method & caveats in the footer). The headline: you own an elite Indian legal network with a small but rapidly growing energy wing — and the energy wing is almost entirely a 2025–26 creation.
Top employers among your connections: Khaitan & Co (171), Trilegal (142), Supreme Court of India (131), EY (113), Cyril Amarchand (109), Shardul Amarchand (108), Google (91), Deloitte (87), AZB (71) — a who's-who of Indian law and consulting. Corrs Chambers Westgarth (Australia) at 45 is your largest single foreign-firm cluster. Geography per contact is not included in LinkedIn's export, so regional splits below use company/title text as a proxy.
| Enlitia searched 12× in 2026 · page followed 24 May '26 | 3 |
| Filipe Fialho — Data Scientist & ML Eng · João Nuno de Sousa — Data Eng · Duarte Lopes — Data Scientist all connected 5–6 May 2026 — deliberate, recent, and one hop from product | |
| Raptor Maps | 0 |
| Pexapark | 0 |
| Amperon | 0 |
| Adjacent energy-analytics Wood Mackenzie 2 — incl. CEO Jason Liu & Ben Hertz-Shargel (Global Head, Grid Transformation) · Aurora Energy Research 3 — incl. Head of Advisory India & Head of Australia · Uplight 2 — incl. Sr. Director Eng. | ~20 |
Three of your four named targets are cold. But the adjacent tier is unusually warm for someone eight weeks into a pivot — a Wood Mackenzie CEO connection is not a normal artifact of a legal network.
Seven findings, each tied to its data and to what it means for the two campaigns you're running: admissions and the international energy-platform search.
| Finding | Evidence (from your archive) | What it means for MBA + exit | |
|---|---|---|---|
| F1 | Your network reads "elite Indian lawyer," not "energy operator." | Legal cluster 5,034 (23.6%) vs energy ~250 (1.2%). Top employers: Khaitan 171, Trilegal 142, Supreme Court 131, CAM 109, SAM 108. | Nobody screening your profile will supply the energy story for you. Your essays and headline must do 100% of the repositioning work — the network won't corroborate it yet. |
| F2 | The pivot is real and datable — roughly 8 weeks old at target level. | "Enlitia" searched 12× in 2026; its 3 engineers added 5–6 May; page followed 24 May. IEA followed Jul '25, CERC Jun '25. 123 of ~250 energy adds post-date CERC start; 59 in 2026. Searches also hit Wood Mackenzie, Uplight, ANDRITZ (8×), Godela, Helin Data. | You have genuine, provable momentum — but it's invisible to anyone but you. Convert private search behavior into public positioning before adcoms and hiring managers look. |
| F3 | You've built a proven outbound engine — aimed at the wrong cluster. | 3,665 invites in H1 2026 → 2,263 name-matched acceptances (~62%). Of those converts: 981 senior (43%), 468 legal (21%), only 53 energy (2.3%). 0 connections at Raptor Maps / Pexapark / Amperon. | A 62% acceptance rate at ~20 invites/day is a weapon. Re-aimed at a 400-name energy-platform list, the same effort yields 200–300 in-sector connections before Round-1 deadlines. |
| F4 | Your public identity is 3.5 years stale — and it's the wrong identity. | 6 posts ever (Nov '22–Jan '23), all media/entertainment law (FIFA brand rights, M&E contracts); last post 17 Jan 2023. 1,594 reactions given vs 6 posts made. 28 endorsements led by Copyright/Compliance/Trademarks; 3 endorsements in the last 18 months. Skills list (51) contains zero energy terms. | You are a heavy consumer, near-zero creator. The gap between claimed thesis and demonstrated expertise is the single widest gap in the file — and the cheapest to close. |
| F5 | Your most defensible asset — the regulator seat — is socially invisible. | Only 18 connections across your own ecosystem (CERC/CEA/MoP/MNRE/APTEL/Grid-India = 14; IEX/PTC/power trading = 4), vs 70+ senior energy contacts outside it. IEA + CEEW think-tank contacts: 13. | "I work at CERC" is your moat, but a moat needs witnesses. Build the regulator ring to 100+ — these are the recommenders, essay validators, and market-intel sources no other applicant can copy. |
| F6 | Admissions surface is seeded; social proof is thin. | 23 admissions-titled contacts (ISB Assoc. Dean; Cambridge Judge Head of MBA Recruitment; Tepper/Heinz/Crimson). 40 of 239 LinkedIn-Learning courses watched are MBA/career-themed. GMAT FE 725 banked Dec 2024. But: no Recommendations file exists in the export, and endorsements have nearly stopped. | Hard signals (score, prep, contacts) are ready; soft signals (recommendations, endorsements, visible advocacy) are missing. Both campaigns need third-party voices manufactured now. |
| F7 | Inbound gravity exists — but it pulls you backward into law. | All 69 conversations started in 2026 were initiated by the other party. Historically 669 of 833 (80%) inbound-first. "legal head hunter" searched 19–22×; "legal associate…" 46× in 2026; job-application history: 286 apps, 271 in 2021–22, 196 legal-titled, 0 product-titled — then a full stop (0 in 2026). | You've already killed the scattergun (good). The residual headhunter searching is the old reflex. Use legal recruiters for optionality and referees — never let them set the narrative. |
2021–22: 271 applications, 196 legal-titled, saved-job trail through Sydney, Dubai, SIAC — the scattergun era. 2023–26: 4, 8, 3, then zero. You stopped spraying and switched to network + MBA. The data confirms the strategy change actually happened.
Top queries: "legal associate…" (46×), NTPC (25×), "legal head hunter" (19×), "Legal Technology Product Manager" (18×), Enlitia (12×), Founder's Office (9×), ANDRITZ (8×), Wood Mackenzie, Uplight, Godela, Helin Data. The old reflex and the new thesis are running side-by-side in your search bar.
Posts made vs reactions given, lifetime. 14,731 accounts followed; hashtags followed since 2020 are litigation/lawyers/lawfirm-era. Comments spiked to 20 in 2025 — you're warming up. The next post you publish will be your first in 3.5 years: make it the thesis.
Added per your request. This panel answers only what the archive can answer: where your network, targets and history already give you coverage. Deadlines, scholarship eligibility (Chevening/Skoll etc.), class age-bands and visa rules are external facts — they belong to your research track, and this map is built to have that research laid on top of it.
| Network coverage per school (people whose listed employer is the school — staff/faculty proxy, not verified alumni): | HBS 9 | IESE 8 | Saïd 4 | Judge 4 | HEC 4 | Wharton 4 | LBS 3 | Kellogg 3 | ISB 3 | INSEAD 2 | Sloan 1 | GSB 1 |
Your H1-2026 outbound engine (3,665 invites, ~62% accepted) currently converts only 2.3% energy. Build a 400-name list — Enlitia/Pexapark/Raptor Maps/Amperon product & strategy staff, plus Aurora, Wood Mackenzie, Uplight, Modo, Kpler, Amperon-adjacent grid-analytics firms — and point the identical effort at it. Open with the warm layer: ask the three Enlitia engineers (Fialho, de Sousa, Lopes) for the intro to their product lead; message Kanani & Prassas (Aurora), Hertz-Shargel (Wood Mackenzie), Dadhich (Uplight).
Rewrite headline/industry/skills to "Energy regulation, built into product" language (add Electricity Markets, Energy Regulation, Product Strategy; retire the pure-litigation clutter). Then a 12-week series translating CERC-world developments into platform implications — e.g. "what this tariff/market-coupling order means for asset-monitoring and PPA-analytics products." Written from public documents, in your own analysis: your seat is the credential, the analysis is the proof.
Systematically connect CERC, CEA, MoP, MNRE, APTEL, Grid-India, IEX, and the think-tank belt (IEA, CEEW — 13 already there). These are the only people who can corroborate "I sit where India's power rules are written" — for essays, recommendations, and eventual employer diligence.
23 admissions-titled contacts — starting with the ISB Associate Dean (Admissions & Careers) and Cambridge Judge's Head of MBA Recruitment & Admissions — plus school-staff clusters (HBS 9, IESE 8, Oxford 30). Convert into 8–10 conversations before Round-1: profile-fit reads, scholarship steers, and the age question answered by humans, not forums.
The export contains zero recommendations and 3 endorsements in 18 months. Commission four recommendations now — a CERC senior, a Naik Naik partner, an Equalaw user/partner, and one energy-sector counterpart — each anchoring a different beam of the thesis. Pair with a targeted endorsement sweep on your five thesis skills.
All 56 files in the 29–30 Jun 2026 export were inventoried; analysis drew primarily on: Connections.csv (21,317 rows, Nov 2019–Jun 2026), Positions, Education, Certifications, TestScores, Skills, Projects, Honors, Volunteering, Endorsements (given/received), Shares, Comments, Reactions, Votes, Company/Member/Hashtag Follows, Invitations (3,837 rows), Job Applications (286), Saved Jobs (87), SearchQueries (234), Job Seeker Preferences, Inferences_about_you, Ad_Targeting, Verifications, and messages.csv (aggregate counts only — 833 conversations; content not quoted). Connection growth by year: 73 · 315 · 2,738 · 4,691 · 2,879 · 3,986 · 4,258 · 2,377 (H1 '26).
SHREYASH — LINKEDIN FORENSIC INSIGHT MAP · EVERY FIGURE COMPUTED FROM THE UPLOADED ARCHIVE · JUL 2026